Ogamon commited on
Commit
850bad8
1 Parent(s): 53b15dc

second commit

Browse files
all_results.json CHANGED
@@ -1,9 +1,10 @@
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  {
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- "epoch": 4.903225806451613,
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- "num_input_tokens_seen": 1207760,
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- "total_flos": 5.438488809413018e+16,
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- "train_loss": 0.4546951471592796,
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- "train_runtime": 2562.7617,
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- "train_samples_per_second": 9.673,
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- "train_steps_per_second": 0.074
 
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  }
 
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  {
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+ "predict_bleu-4": 85.9556957278481,
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+ "predict_model_preparation_time": 0.0049,
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+ "predict_rouge-1": 92.87974683544304,
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+ "predict_rouge-2": 0.0,
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+ "predict_rouge-l": 92.87974683544304,
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+ "predict_runtime": 8.8919,
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+ "predict_samples_per_second": 140.915,
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+ "predict_steps_per_second": 8.885
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  }
generated_predictions.jsonl ADDED
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llamaboard_config.yaml CHANGED
@@ -1,5 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
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  top.booster: auto
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- top.checkpoint_path: null
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  top.finetuning_type: full
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  top.model_name: LLaMA3.1-8B-Chat
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  top.quantization_bit: none
@@ -7,61 +18,3 @@ top.quantization_method: bitsandbytes
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  top.rope_scaling: none
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  top.template: llama3
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  top.visual_inputs: false
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- train.additional_target: ''
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- train.badam_mode: layer
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- train.badam_switch_interval: 50
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- train.badam_switch_mode: ascending
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- train.badam_update_ratio: 0.05
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- train.batch_size: 2
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- train.compute_type: bf16
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- train.create_new_adapter: false
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- train.cutoff_len: 1024
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- train.dataset:
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- - truth_train_0716_2
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- train.dataset_dir: data
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- train.ds_offload: false
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- train.ds_stage: '2'
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- train.freeze_extra_modules: ''
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- train.freeze_trainable_layers: 2
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- train.freeze_trainable_modules: all
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- train.galore_rank: 16
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- train.galore_scale: 0.25
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- train.galore_target: all
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- train.galore_update_interval: 200
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- train.gradient_accumulation_steps: 8
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- train.learning_rate: 5e-6
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- train.logging_steps: 1
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- train.lora_alpha: 16
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- train.lora_dropout: 0
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- train.lora_rank: 8
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- train.lora_target: ''
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- train.loraplus_lr_ratio: 0
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- train.lr_scheduler_type: cosine
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- train.mask_history: false
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- train.max_grad_norm: '1.0'
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- train.max_samples: '100000'
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- train.neat_packing: false
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- train.neftune_alpha: 0
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- train.num_train_epochs: '5.0'
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- train.optim: adamw_torch
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- train.packing: false
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- train.ppo_score_norm: false
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- train.ppo_whiten_rewards: false
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- train.pref_beta: 0.1
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- train.pref_ftx: 0
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- train.pref_loss: sigmoid
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- train.report_to: false
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- train.resize_vocab: false
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- train.reward_model: null
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- train.save_steps: 5000
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- train.shift_attn: false
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- train.train_on_prompt: false
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- train.training_stage: Supervised Fine-Tuning
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- train.use_badam: false
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- train.use_dora: false
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- train.use_galore: false
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- train.use_llama_pro: false
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- train.use_pissa: false
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- train.use_rslora: false
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- train.val_size: 0
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- train.warmup_steps: 10
 
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+ eval.batch_size: 2
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+ eval.cutoff_len: 1024
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+ eval.dataset:
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+ - truth_dev_0716_2
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+ eval.dataset_dir: data
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+ eval.max_new_tokens: 512
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+ eval.max_samples: '100000'
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+ eval.output_dir: eval_2024-07-30-02-47-53_llama3.1_truthqa_bench2
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+ eval.predict: true
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+ eval.temperature: 0.95
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+ eval.top_p: 0.7
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  top.booster: auto
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+ top.checkpoint_path: train_2024-07-30-02-47-53_llama3.1_truthqa_bench2
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  top.finetuning_type: full
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  top.model_name: LLaMA3.1-8B-Chat
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  top.quantization_bit: none
 
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  top.rope_scaling: none
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  top.template: llama3
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  top.visual_inputs: false
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
predict_results.json ADDED
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+ {
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+ "predict_bleu-4": 85.9556957278481,
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+ "predict_model_preparation_time": 0.0049,
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+ "predict_rouge-1": 92.87974683544304,
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+ "predict_rouge-2": 0.0,
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+ "predict_rouge-l": 92.87974683544304,
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+ "predict_runtime": 8.8919,
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+ "predict_samples_per_second": 140.915,
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+ "predict_steps_per_second": 8.885
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+ }
running_log.txt CHANGED
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- 07/30/2024 02:49:08 - INFO - llamafactory.hparams.parser - Process rank: 7, device: cuda:7, n_gpu: 1, distributed training: True, compute dtype: torch.bfloat16
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- 07/30/2024 02:49:08 - INFO - llamafactory.hparams.parser - Process rank: 2, device: cuda:2, n_gpu: 1, distributed training: True, compute dtype: torch.bfloat16
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- 07/30/2024 02:49:08 - INFO - llamafactory.hparams.parser - Process rank: 6, device: cuda:6, n_gpu: 1, distributed training: True, compute dtype: torch.bfloat16
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- 07/30/2024 02:49:08 - INFO - llamafactory.hparams.parser - Process rank: 1, device: cuda:1, n_gpu: 1, distributed training: True, compute dtype: torch.bfloat16
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- 07/30/2024 02:49:09 - INFO - llamafactory.data.template - Replace eos token: <|eot_id|>
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- [INFO|tokenization_utils_base.py:2289] 2024-07-30 02:49:09,083 >> loading file tokenizer.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3.1-8B-Instruct/snapshots/b2a4d0f33b41fcd59a6d31662cc63b8d53367e1e/tokenizer.json
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- [INFO|tokenization_utils_base.py:2289] 2024-07-30 02:49:09,083 >> loading file added_tokens.json from cache at None
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- [INFO|tokenization_utils_base.py:2289] 2024-07-30 02:49:09,083 >> loading file special_tokens_map.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3.1-8B-Instruct/snapshots/b2a4d0f33b41fcd59a6d31662cc63b8d53367e1e/special_tokens_map.json
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- [INFO|tokenization_utils_base.py:2289] 2024-07-30 02:49:09,083 >> loading file tokenizer_config.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3.1-8B-Instruct/snapshots/b2a4d0f33b41fcd59a6d31662cc63b8d53367e1e/tokenizer_config.json
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- [INFO|tokenization_utils_base.py:2533] 2024-07-30 02:49:09,345 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
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- [INFO|template.py:270] 2024-07-30 02:49:09,345 >> Replace eos token: <|eot_id|>
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- [INFO|loader.py:52] 2024-07-30 02:49:09,346 >> Loading dataset 0716_truthfulqa_benchmark_train_2.json...
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- 07/30/2024 02:49:09 - INFO - llamafactory.data.template - Replace eos token: <|eot_id|>
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- 07/30/2024 02:49:11 - INFO - llamafactory.data.loader - Loading dataset 0716_truthfulqa_benchmark_train_2.json...
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- 07/30/2024 02:49:11 - INFO - llamafactory.data.loader - Loading dataset 0716_truthfulqa_benchmark_train_2.json...
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- [INFO|configuration_utils.py:733] 2024-07-30 02:49:14,919 >> loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3.1-8B-Instruct/snapshots/b2a4d0f33b41fcd59a6d31662cc63b8d53367e1e/config.json
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- [INFO|configuration_utils.py:800] 2024-07-30 02:49:14,925 >> Model config LlamaConfig {
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- "_name_or_path": "meta-llama/Meta-Llama-3.1-8B-Instruct",
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  "architectures": [
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  "LlamaForCausalLM"
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  ],
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  "tie_word_embeddings": false,
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  "torch_dtype": "bfloat16",
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  "transformers_version": "4.43.3",
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- "use_cache": true,
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  "vocab_size": 128256
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  }
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- [INFO|modeling_utils.py:3634] 2024-07-30 02:49:14,976 >> loading weights file model.safetensors from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3.1-8B-Instruct/snapshots/b2a4d0f33b41fcd59a6d31662cc63b8d53367e1e/model.safetensors.index.json
 
 
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- [INFO|modeling_utils.py:1572] 2024-07-30 02:49:14,978 >> Instantiating LlamaForCausalLM model under default dtype torch.bfloat16.
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- [INFO|configuration_utils.py:1038] 2024-07-30 02:49:14,981 >> Generate config GenerationConfig {
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  "bos_token_id": 128000,
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  "eos_token_id": [
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  }
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- [INFO|modeling_utils.py:4463] 2024-07-30 02:49:19,162 >> All model checkpoint weights were used when initializing LlamaForCausalLM.
 
 
 
 
 
 
 
 
 
 
 
 
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- [INFO|modeling_utils.py:4471] 2024-07-30 02:49:19,162 >> All the weights of LlamaForCausalLM were initialized from the model checkpoint at meta-llama/Meta-Llama-3.1-8B-Instruct.
 
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- [INFO|configuration_utils.py:993] 2024-07-30 02:49:19,337 >> loading configuration file generation_config.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3.1-8B-Instruct/snapshots/b2a4d0f33b41fcd59a6d31662cc63b8d53367e1e/generation_config.json
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  "bos_token_id": 128000,
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  "do_sample": true,
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  "eos_token_id": [
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- [INFO|checkpointing.py:103] 2024-07-30 02:49:19,344 >> Gradient checkpointing enabled.
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- [INFO|attention.py:84] 2024-07-30 02:49:19,345 >> Using torch SDPA for faster training and inference.
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- [INFO|adapter.py:302] 2024-07-30 02:49:19,345 >> Upcasting trainable params to float32.
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- [INFO|adapter.py:48] 2024-07-30 02:49:19,345 >> Fine-tuning method: Full
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- [INFO|loader.py:196] 2024-07-30 02:49:19,389 >> trainable params: 8,030,261,248 || all params: 8,030,261,248 || trainable%: 100.0000
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267
- [INFO|callbacks.py:310] 2024-07-30 02:52:08,132 >> {'loss': 1.1284, 'learning_rate': 4.9996e-06, 'epoch': 0.28, 'throughput': 478.35}
268
-
269
- [INFO|callbacks.py:310] 2024-07-30 02:52:21,287 >> {'loss': 1.1272, 'learning_rate': 4.9985e-06, 'epoch': 0.31, 'throughput': 479.03}
270
-
271
- [INFO|callbacks.py:310] 2024-07-30 02:52:34,460 >> {'loss': 0.9501, 'learning_rate': 4.9966e-06, 'epoch': 0.34, 'throughput': 479.08}
272
-
273
- [INFO|callbacks.py:310] 2024-07-30 02:52:47,615 >> {'loss': 0.4610, 'learning_rate': 4.9939e-06, 'epoch': 0.36, 'throughput': 478.92}
274
-
275
- [INFO|callbacks.py:310] 2024-07-30 02:53:00,776 >> {'loss': 1.2016, 'learning_rate': 4.9905e-06, 'epoch': 0.39, 'throughput': 479.89}
276
-
277
- [INFO|callbacks.py:310] 2024-07-30 02:53:13,956 >> {'loss': 0.3310, 'learning_rate': 4.9863e-06, 'epoch': 0.41, 'throughput': 480.39}
278
-
279
- [INFO|callbacks.py:310] 2024-07-30 02:53:27,114 >> {'loss': 0.3565, 'learning_rate': 4.9814e-06, 'epoch': 0.44, 'throughput': 480.60}
280
-
281
- [INFO|callbacks.py:310] 2024-07-30 02:53:40,291 >> {'loss': 0.6088, 'learning_rate': 4.9757e-06, 'epoch': 0.46, 'throughput': 480.01}
282
-
283
- [INFO|callbacks.py:310] 2024-07-30 02:53:53,463 >> {'loss': 0.2701, 'learning_rate': 4.9692e-06, 'epoch': 0.49, 'throughput': 480.13}
284
-
285
- [INFO|callbacks.py:310] 2024-07-30 02:54:06,625 >> {'loss': 0.7005, 'learning_rate': 4.9620e-06, 'epoch': 0.52, 'throughput': 480.07}
286
-
287
- [INFO|callbacks.py:310] 2024-07-30 02:54:19,803 >> {'loss': 0.3424, 'learning_rate': 4.9541e-06, 'epoch': 0.54, 'throughput': 481.03}
288
-
289
- [INFO|callbacks.py:310] 2024-07-30 02:54:32,946 >> {'loss': 0.6274, 'learning_rate': 4.9454e-06, 'epoch': 0.57, 'throughput': 480.58}
290
-
291
- [INFO|callbacks.py:310] 2024-07-30 02:54:46,125 >> {'loss': 0.4183, 'learning_rate': 4.9359e-06, 'epoch': 0.59, 'throughput': 480.64}
292
-
293
- [INFO|callbacks.py:310] 2024-07-30 02:54:59,279 >> {'loss': 0.1517, 'learning_rate': 4.9257e-06, 'epoch': 0.62, 'throughput': 481.29}
294
-
295
- [INFO|callbacks.py:310] 2024-07-30 02:55:12,444 >> {'loss': 0.1906, 'learning_rate': 4.9148e-06, 'epoch': 0.65, 'throughput': 480.85}
296
-
297
- [INFO|callbacks.py:310] 2024-07-30 02:55:25,606 >> {'loss': 0.1537, 'learning_rate': 4.9032e-06, 'epoch': 0.67, 'throughput': 480.78}
298
-
299
- [INFO|callbacks.py:310] 2024-07-30 02:55:38,769 >> {'loss': 0.1957, 'learning_rate': 4.8908e-06, 'epoch': 0.70, 'throughput': 481.34}
300
-
301
- [INFO|callbacks.py:310] 2024-07-30 02:55:51,936 >> {'loss': 0.3026, 'learning_rate': 4.8776e-06, 'epoch': 0.72, 'throughput': 481.25}
302
-
303
- [INFO|callbacks.py:310] 2024-07-30 02:56:05,100 >> {'loss': 0.2031, 'learning_rate': 4.8638e-06, 'epoch': 0.75, 'throughput': 481.25}
304
-
305
- [INFO|callbacks.py:310] 2024-07-30 02:56:18,268 >> {'loss': 0.1461, 'learning_rate': 4.8492e-06, 'epoch': 0.77, 'throughput': 481.53}
306
-
307
- [INFO|callbacks.py:310] 2024-07-30 02:56:31,447 >> {'loss': 0.1873, 'learning_rate': 4.8340e-06, 'epoch': 0.80, 'throughput': 481.00}
308
-
309
- [INFO|callbacks.py:310] 2024-07-30 02:56:44,603 >> {'loss': 0.1388, 'learning_rate': 4.8180e-06, 'epoch': 0.83, 'throughput': 480.75}
310
-
311
- [INFO|callbacks.py:310] 2024-07-30 02:56:57,774 >> {'loss': 0.1127, 'learning_rate': 4.8013e-06, 'epoch': 0.85, 'throughput': 481.16}
312
-
313
- [INFO|callbacks.py:310] 2024-07-30 02:57:10,949 >> {'loss': 0.1243, 'learning_rate': 4.7839e-06, 'epoch': 0.88, 'throughput': 480.87}
314
-
315
- [INFO|callbacks.py:310] 2024-07-30 02:57:24,122 >> {'loss': 0.0969, 'learning_rate': 4.7658e-06, 'epoch': 0.90, 'throughput': 480.63}
316
-
317
- [INFO|callbacks.py:310] 2024-07-30 02:57:37,282 >> {'loss': 0.0890, 'learning_rate': 4.7470e-06, 'epoch': 0.93, 'throughput': 480.62}
318
-
319
- [INFO|callbacks.py:310] 2024-07-30 02:57:50,444 >> {'loss': 0.1703, 'learning_rate': 4.7275e-06, 'epoch': 0.95, 'throughput': 481.20}
320
-
321
- [INFO|callbacks.py:310] 2024-07-30 02:58:03,606 >> {'loss': 0.1132, 'learning_rate': 4.7074e-06, 'epoch': 0.98, 'throughput': 481.46}
322
-
323
- [INFO|callbacks.py:310] 2024-07-30 02:58:16,767 >> {'loss': 0.1294, 'learning_rate': 4.6865e-06, 'epoch': 1.01, 'throughput': 481.77}
324
-
325
- [INFO|callbacks.py:310] 2024-07-30 02:58:29,908 >> {'loss': 0.0881, 'learning_rate': 4.6651e-06, 'epoch': 1.03, 'throughput': 481.78}
326
-
327
- [INFO|callbacks.py:310] 2024-07-30 02:58:43,077 >> {'loss': 0.0504, 'learning_rate': 4.6429e-06, 'epoch': 1.06, 'throughput': 481.55}
328
-
329
- [INFO|callbacks.py:310] 2024-07-30 02:58:56,238 >> {'loss': 0.0723, 'learning_rate': 4.6201e-06, 'epoch': 1.08, 'throughput': 481.72}
330
-
331
- [INFO|callbacks.py:310] 2024-07-30 02:59:09,398 >> {'loss': 0.0726, 'learning_rate': 4.5967e-06, 'epoch': 1.11, 'throughput': 481.69}
332
-
333
- [INFO|callbacks.py:310] 2024-07-30 02:59:22,561 >> {'loss': 0.1355, 'learning_rate': 4.5726e-06, 'epoch': 1.14, 'throughput': 481.60}
334
-
335
- [INFO|callbacks.py:310] 2024-07-30 02:59:35,735 >> {'loss': 0.0713, 'learning_rate': 4.5479e-06, 'epoch': 1.16, 'throughput': 481.51}
336
-
337
- [INFO|callbacks.py:310] 2024-07-30 02:59:48,896 >> {'loss': 0.0796, 'learning_rate': 4.5225e-06, 'epoch': 1.19, 'throughput': 481.50}
338
-
339
- [INFO|callbacks.py:310] 2024-07-30 03:00:02,045 >> {'loss': 0.0778, 'learning_rate': 4.4966e-06, 'epoch': 1.21, 'throughput': 481.46}
340
-
341
- [INFO|callbacks.py:310] 2024-07-30 03:00:15,214 >> {'loss': 0.0606, 'learning_rate': 4.4700e-06, 'epoch': 1.24, 'throughput': 481.40}
342
-
343
- [INFO|callbacks.py:310] 2024-07-30 03:00:28,372 >> {'loss': 0.0411, 'learning_rate': 4.4429e-06, 'epoch': 1.26, 'throughput': 481.53}
344
-
345
- [INFO|callbacks.py:310] 2024-07-30 03:00:41,534 >> {'loss': 0.0773, 'learning_rate': 4.4151e-06, 'epoch': 1.29, 'throughput': 481.53}
346
-
347
- [INFO|callbacks.py:310] 2024-07-30 03:00:54,678 >> {'loss': 0.0355, 'learning_rate': 4.3868e-06, 'epoch': 1.32, 'throughput': 481.73}
348
-
349
- [INFO|callbacks.py:310] 2024-07-30 03:01:07,849 >> {'loss': 0.0607, 'learning_rate': 4.3579e-06, 'epoch': 1.34, 'throughput': 481.48}
350
-
351
- [INFO|callbacks.py:310] 2024-07-30 03:01:21,013 >> {'loss': 0.0542, 'learning_rate': 4.3284e-06, 'epoch': 1.37, 'throughput': 481.43}
352
-
353
- [INFO|callbacks.py:310] 2024-07-30 03:01:34,182 >> {'loss': 0.0629, 'learning_rate': 4.2983e-06, 'epoch': 1.39, 'throughput': 481.42}
354
-
355
- [INFO|callbacks.py:310] 2024-07-30 03:01:47,353 >> {'loss': 0.0519, 'learning_rate': 4.2678e-06, 'epoch': 1.42, 'throughput': 481.73}
356
-
357
- [INFO|callbacks.py:310] 2024-07-30 03:02:00,520 >> {'loss': 0.0481, 'learning_rate': 4.2366e-06, 'epoch': 1.45, 'throughput': 481.67}
358
-
359
- [INFO|callbacks.py:310] 2024-07-30 03:02:13,678 >> {'loss': 0.0659, 'learning_rate': 4.2050e-06, 'epoch': 1.47, 'throughput': 481.67}
360
-
361
- [INFO|callbacks.py:310] 2024-07-30 03:02:26,831 >> {'loss': 0.0980, 'learning_rate': 4.1728e-06, 'epoch': 1.50, 'throughput': 482.09}
362
-
363
- [INFO|callbacks.py:310] 2024-07-30 03:02:40,005 >> {'loss': 0.0411, 'learning_rate': 4.1401e-06, 'epoch': 1.52, 'throughput': 482.24}
364
-
365
- [INFO|callbacks.py:310] 2024-07-30 03:02:53,178 >> {'loss': 0.0396, 'learning_rate': 4.1070e-06, 'epoch': 1.55, 'throughput': 481.97}
366
-
367
- [INFO|callbacks.py:310] 2024-07-30 03:03:06,330 >> {'loss': 0.0413, 'learning_rate': 4.0733e-06, 'epoch': 1.57, 'throughput': 481.73}
368
-
369
- [INFO|callbacks.py:310] 2024-07-30 03:03:19,497 >> {'loss': 0.1195, 'learning_rate': 4.0392e-06, 'epoch': 1.60, 'throughput': 482.02}
370
-
371
- [INFO|callbacks.py:310] 2024-07-30 03:03:32,670 >> {'loss': 0.0534, 'learning_rate': 4.0045e-06, 'epoch': 1.63, 'throughput': 482.06}
372
-
373
- [INFO|callbacks.py:310] 2024-07-30 03:03:45,839 >> {'loss': 0.0662, 'learning_rate': 3.9695e-06, 'epoch': 1.65, 'throughput': 481.93}
374
-
375
- [INFO|callbacks.py:310] 2024-07-30 03:03:59,009 >> {'loss': 0.0462, 'learning_rate': 3.9339e-06, 'epoch': 1.68, 'throughput': 481.86}
376
-
377
- [INFO|callbacks.py:310] 2024-07-30 03:04:12,160 >> {'loss': 0.0899, 'learning_rate': 3.8980e-06, 'epoch': 1.70, 'throughput': 481.90}
378
-
379
- [INFO|callbacks.py:310] 2024-07-30 03:04:25,334 >> {'loss': 0.0691, 'learning_rate': 3.8616e-06, 'epoch': 1.73, 'throughput': 482.08}
380
-
381
- [INFO|callbacks.py:310] 2024-07-30 03:04:38,487 >> {'loss': 0.1022, 'learning_rate': 3.8248e-06, 'epoch': 1.75, 'throughput': 482.24}
382
-
383
- [INFO|callbacks.py:310] 2024-07-30 03:04:51,658 >> {'loss': 0.1062, 'learning_rate': 3.7876e-06, 'epoch': 1.78, 'throughput': 482.17}
384
-
385
- [INFO|callbacks.py:310] 2024-07-30 03:05:04,814 >> {'loss': 0.0491, 'learning_rate': 3.7500e-06, 'epoch': 1.81, 'throughput': 482.44}
386
-
387
- [INFO|callbacks.py:310] 2024-07-30 03:05:17,972 >> {'loss': 0.1507, 'learning_rate': 3.7120e-06, 'epoch': 1.83, 'throughput': 482.42}
388
-
389
- [INFO|callbacks.py:310] 2024-07-30 03:05:31,123 >> {'loss': 0.1234, 'learning_rate': 3.6737e-06, 'epoch': 1.86, 'throughput': 482.31}
390
-
391
- [INFO|callbacks.py:310] 2024-07-30 03:05:44,271 >> {'loss': 0.0450, 'learning_rate': 3.6350e-06, 'epoch': 1.88, 'throughput': 482.26}
392
-
393
- [INFO|callbacks.py:310] 2024-07-30 03:05:57,439 >> {'loss': 0.0615, 'learning_rate': 3.5959e-06, 'epoch': 1.91, 'throughput': 482.50}
394
-
395
- [INFO|callbacks.py:310] 2024-07-30 03:06:10,604 >> {'loss': 0.1961, 'learning_rate': 3.5565e-06, 'epoch': 1.94, 'throughput': 482.59}
396
-
397
- [INFO|callbacks.py:310] 2024-07-30 03:06:23,764 >> {'loss': 0.2311, 'learning_rate': 3.5168e-06, 'epoch': 1.96, 'throughput': 482.60}
398
-
399
- [INFO|callbacks.py:310] 2024-07-30 03:06:36,916 >> {'loss': 0.1556, 'learning_rate': 3.4768e-06, 'epoch': 1.99, 'throughput': 482.48}
400
-
401
- [INFO|callbacks.py:310] 2024-07-30 03:06:50,068 >> {'loss': 0.0626, 'learning_rate': 3.4365e-06, 'epoch': 2.01, 'throughput': 482.38}
402
-
403
- [INFO|callbacks.py:310] 2024-07-30 03:07:03,233 >> {'loss': 0.0197, 'learning_rate': 3.3959e-06, 'epoch': 2.04, 'throughput': 482.41}
404
-
405
- [INFO|callbacks.py:310] 2024-07-30 03:07:16,401 >> {'loss': 0.0057, 'learning_rate': 3.3551e-06, 'epoch': 2.06, 'throughput': 482.65}
406
-
407
- [INFO|callbacks.py:310] 2024-07-30 03:07:29,571 >> {'loss': 0.0290, 'learning_rate': 3.3139e-06, 'epoch': 2.09, 'throughput': 482.53}
408
-
409
- [INFO|callbacks.py:310] 2024-07-30 03:07:42,734 >> {'loss': 0.0593, 'learning_rate': 3.2725e-06, 'epoch': 2.12, 'throughput': 482.74}
410
-
411
- [INFO|callbacks.py:310] 2024-07-30 03:07:55,878 >> {'loss': 0.0455, 'learning_rate': 3.2309e-06, 'epoch': 2.14, 'throughput': 482.77}
412
-
413
- [INFO|callbacks.py:310] 2024-07-30 03:08:09,034 >> {'loss': 0.0325, 'learning_rate': 3.1891e-06, 'epoch': 2.17, 'throughput': 482.74}
414
-
415
- [INFO|callbacks.py:310] 2024-07-30 03:08:22,192 >> {'loss': 0.0071, 'learning_rate': 3.1470e-06, 'epoch': 2.19, 'throughput': 482.90}
416
-
417
- [INFO|callbacks.py:310] 2024-07-30 03:08:35,352 >> {'loss': 0.0336, 'learning_rate': 3.1048e-06, 'epoch': 2.22, 'throughput': 482.86}
418
-
419
- [INFO|callbacks.py:310] 2024-07-30 03:08:48,514 >> {'loss': 0.0389, 'learning_rate': 3.0624e-06, 'epoch': 2.25, 'throughput': 482.92}
420
-
421
- [INFO|callbacks.py:310] 2024-07-30 03:09:01,669 >> {'loss': 0.0016, 'learning_rate': 3.0198e-06, 'epoch': 2.27, 'throughput': 482.87}
422
-
423
- [INFO|callbacks.py:310] 2024-07-30 03:09:14,848 >> {'loss': 0.0625, 'learning_rate': 2.9770e-06, 'epoch': 2.30, 'throughput': 483.05}
424
-
425
- [INFO|callbacks.py:310] 2024-07-30 03:09:27,996 >> {'loss': 0.0201, 'learning_rate': 2.9341e-06, 'epoch': 2.32, 'throughput': 482.95}
426
-
427
- [INFO|callbacks.py:310] 2024-07-30 03:09:41,158 >> {'loss': 0.0126, 'learning_rate': 2.8911e-06, 'epoch': 2.35, 'throughput': 482.79}
428
-
429
- [INFO|callbacks.py:310] 2024-07-30 03:09:54,341 >> {'loss': 0.0148, 'learning_rate': 2.8479e-06, 'epoch': 2.37, 'throughput': 482.91}
430
-
431
- [INFO|callbacks.py:310] 2024-07-30 03:10:07,511 >> {'loss': 0.0140, 'learning_rate': 2.8047e-06, 'epoch': 2.40, 'throughput': 482.83}
432
-
433
- [INFO|callbacks.py:310] 2024-07-30 03:10:20,674 >> {'loss': 0.0096, 'learning_rate': 2.7613e-06, 'epoch': 2.43, 'throughput': 482.82}
434
-
435
- [INFO|callbacks.py:310] 2024-07-30 03:10:33,834 >> {'loss': 0.0249, 'learning_rate': 2.7179e-06, 'epoch': 2.45, 'throughput': 482.82}
436
-
437
- [INFO|callbacks.py:310] 2024-07-30 03:10:47,009 >> {'loss': 0.0358, 'learning_rate': 2.6744e-06, 'epoch': 2.48, 'throughput': 482.76}
438
-
439
- [INFO|callbacks.py:310] 2024-07-30 03:11:00,178 >> {'loss': 0.0494, 'learning_rate': 2.6308e-06, 'epoch': 2.50, 'throughput': 482.67}
440
-
441
- [INFO|callbacks.py:310] 2024-07-30 03:11:13,329 >> {'loss': 0.0092, 'learning_rate': 2.5872e-06, 'epoch': 2.53, 'throughput': 482.63}
442
-
443
- [INFO|callbacks.py:310] 2024-07-30 03:11:26,479 >> {'loss': 0.0215, 'learning_rate': 2.5436e-06, 'epoch': 2.55, 'throughput': 482.59}
444
-
445
- [INFO|callbacks.py:310] 2024-07-30 03:11:39,631 >> {'loss': 0.0122, 'learning_rate': 2.5000e-06, 'epoch': 2.58, 'throughput': 482.73}
446
-
447
- [INFO|callbacks.py:310] 2024-07-30 03:11:52,780 >> {'loss': 0.0296, 'learning_rate': 2.4564e-06, 'epoch': 2.61, 'throughput': 482.73}
448
-
449
- [INFO|callbacks.py:310] 2024-07-30 03:12:05,936 >> {'loss': 0.0089, 'learning_rate': 2.4128e-06, 'epoch': 2.63, 'throughput': 482.78}
450
-
451
- [INFO|callbacks.py:310] 2024-07-30 03:12:19,112 >> {'loss': 0.0406, 'learning_rate': 2.3692e-06, 'epoch': 2.66, 'throughput': 482.65}
452
-
453
- [INFO|callbacks.py:310] 2024-07-30 03:12:32,273 >> {'loss': 0.0114, 'learning_rate': 2.3256e-06, 'epoch': 2.68, 'throughput': 482.82}
454
-
455
- [INFO|callbacks.py:310] 2024-07-30 03:12:45,431 >> {'loss': 0.0396, 'learning_rate': 2.2821e-06, 'epoch': 2.71, 'throughput': 482.81}
456
-
457
- [INFO|callbacks.py:310] 2024-07-30 03:12:58,595 >> {'loss': 0.0077, 'learning_rate': 2.2387e-06, 'epoch': 2.74, 'throughput': 482.67}
458
-
459
- [INFO|callbacks.py:310] 2024-07-30 03:13:11,749 >> {'loss': 0.0044, 'learning_rate': 2.1953e-06, 'epoch': 2.76, 'throughput': 482.63}
460
-
461
- [INFO|callbacks.py:310] 2024-07-30 03:13:24,906 >> {'loss': 0.0045, 'learning_rate': 2.1521e-06, 'epoch': 2.79, 'throughput': 482.54}
462
-
463
- [INFO|callbacks.py:310] 2024-07-30 03:13:38,052 >> {'loss': 0.0405, 'learning_rate': 2.1089e-06, 'epoch': 2.81, 'throughput': 482.51}
464
-
465
- [INFO|callbacks.py:310] 2024-07-30 03:13:51,205 >> {'loss': 0.0225, 'learning_rate': 2.0659e-06, 'epoch': 2.84, 'throughput': 482.55}
466
-
467
- [INFO|callbacks.py:310] 2024-07-30 03:14:04,369 >> {'loss': 0.0415, 'learning_rate': 2.0230e-06, 'epoch': 2.86, 'throughput': 482.50}
468
-
469
- [INFO|callbacks.py:310] 2024-07-30 03:14:17,523 >> {'loss': 0.0173, 'learning_rate': 1.9802e-06, 'epoch': 2.89, 'throughput': 482.45}
470
-
471
- [INFO|callbacks.py:310] 2024-07-30 03:14:30,685 >> {'loss': 0.0005, 'learning_rate': 1.9376e-06, 'epoch': 2.92, 'throughput': 482.38}
472
-
473
- [INFO|callbacks.py:310] 2024-07-30 03:14:43,845 >> {'loss': 0.0306, 'learning_rate': 1.8952e-06, 'epoch': 2.94, 'throughput': 482.57}
474
-
475
- [INFO|callbacks.py:310] 2024-07-30 03:14:57,012 >> {'loss': 0.0422, 'learning_rate': 1.8530e-06, 'epoch': 2.97, 'throughput': 482.66}
476
-
477
- [INFO|callbacks.py:310] 2024-07-30 03:15:10,157 >> {'loss': 0.0472, 'learning_rate': 1.8109e-06, 'epoch': 2.99, 'throughput': 482.55}
478
-
479
- [INFO|callbacks.py:310] 2024-07-30 03:15:23,306 >> {'loss': 0.0259, 'learning_rate': 1.7691e-06, 'epoch': 3.02, 'throughput': 482.50}
480
-
481
- [INFO|callbacks.py:310] 2024-07-30 03:15:36,475 >> {'loss': 0.0029, 'learning_rate': 1.7275e-06, 'epoch': 3.05, 'throughput': 482.46}
482
-
483
- [INFO|callbacks.py:310] 2024-07-30 03:15:49,636 >> {'loss': 0.0350, 'learning_rate': 1.6861e-06, 'epoch': 3.07, 'throughput': 482.46}
484
-
485
- [INFO|callbacks.py:310] 2024-07-30 03:16:02,800 >> {'loss': 0.0015, 'learning_rate': 1.6449e-06, 'epoch': 3.10, 'throughput': 482.26}
486
-
487
- [INFO|callbacks.py:310] 2024-07-30 03:16:15,954 >> {'loss': 0.0006, 'learning_rate': 1.6041e-06, 'epoch': 3.12, 'throughput': 482.20}
488
-
489
- [INFO|callbacks.py:310] 2024-07-30 03:16:29,114 >> {'loss': 0.0143, 'learning_rate': 1.5635e-06, 'epoch': 3.15, 'throughput': 482.19}
490
-
491
- [INFO|callbacks.py:310] 2024-07-30 03:16:42,268 >> {'loss': 0.0219, 'learning_rate': 1.5232e-06, 'epoch': 3.17, 'throughput': 482.19}
492
-
493
- [INFO|callbacks.py:310] 2024-07-30 03:16:55,411 >> {'loss': 0.0074, 'learning_rate': 1.4832e-06, 'epoch': 3.20, 'throughput': 482.31}
494
-
495
- [INFO|callbacks.py:310] 2024-07-30 03:17:08,589 >> {'loss': 0.0052, 'learning_rate': 1.4435e-06, 'epoch': 3.23, 'throughput': 482.23}
496
-
497
- [INFO|callbacks.py:310] 2024-07-30 03:17:21,739 >> {'loss': 0.0013, 'learning_rate': 1.4041e-06, 'epoch': 3.25, 'throughput': 482.19}
498
-
499
- [INFO|callbacks.py:310] 2024-07-30 03:17:34,901 >> {'loss': 0.0018, 'learning_rate': 1.3650e-06, 'epoch': 3.28, 'throughput': 482.26}
500
-
501
- [INFO|callbacks.py:310] 2024-07-30 03:17:48,057 >> {'loss': 0.0077, 'learning_rate': 1.3263e-06, 'epoch': 3.30, 'throughput': 482.22}
502
-
503
- [INFO|callbacks.py:310] 2024-07-30 03:18:01,209 >> {'loss': 0.0138, 'learning_rate': 1.2880e-06, 'epoch': 3.33, 'throughput': 482.24}
504
-
505
- [INFO|callbacks.py:310] 2024-07-30 03:18:14,360 >> {'loss': 0.0102, 'learning_rate': 1.2500e-06, 'epoch': 3.35, 'throughput': 482.29}
506
-
507
- [INFO|callbacks.py:310] 2024-07-30 03:18:27,523 >> {'loss': 0.0067, 'learning_rate': 1.2124e-06, 'epoch': 3.38, 'throughput': 482.41}
508
-
509
- [INFO|callbacks.py:310] 2024-07-30 03:18:40,673 >> {'loss': 0.0056, 'learning_rate': 1.1752e-06, 'epoch': 3.41, 'throughput': 482.43}
510
-
511
- [INFO|callbacks.py:310] 2024-07-30 03:18:53,846 >> {'loss': 0.0066, 'learning_rate': 1.1384e-06, 'epoch': 3.43, 'throughput': 482.59}
512
-
513
- [INFO|callbacks.py:310] 2024-07-30 03:19:07,002 >> {'loss': 0.0033, 'learning_rate': 1.1020e-06, 'epoch': 3.46, 'throughput': 482.61}
514
-
515
- [INFO|callbacks.py:310] 2024-07-30 03:19:20,156 >> {'loss': 0.0008, 'learning_rate': 1.0661e-06, 'epoch': 3.48, 'throughput': 482.56}
516
-
517
- [INFO|callbacks.py:310] 2024-07-30 03:19:33,324 >> {'loss': 0.0027, 'learning_rate': 1.0305e-06, 'epoch': 3.51, 'throughput': 482.56}
518
-
519
- [INFO|callbacks.py:310] 2024-07-30 03:19:46,477 >> {'loss': 0.0021, 'learning_rate': 9.9546e-07, 'epoch': 3.54, 'throughput': 482.46}
520
-
521
- [INFO|callbacks.py:310] 2024-07-30 03:19:59,648 >> {'loss': 0.0008, 'learning_rate': 9.6085e-07, 'epoch': 3.56, 'throughput': 482.42}
522
-
523
- [INFO|callbacks.py:310] 2024-07-30 03:20:12,805 >> {'loss': 0.0051, 'learning_rate': 9.2670e-07, 'epoch': 3.59, 'throughput': 482.52}
524
-
525
- [INFO|callbacks.py:310] 2024-07-30 03:20:25,967 >> {'loss': 0.0026, 'learning_rate': 8.9303e-07, 'epoch': 3.61, 'throughput': 482.52}
526
-
527
- [INFO|callbacks.py:310] 2024-07-30 03:20:39,143 >> {'loss': 0.0041, 'learning_rate': 8.5985e-07, 'epoch': 3.64, 'throughput': 482.51}
528
-
529
- [INFO|callbacks.py:310] 2024-07-30 03:20:52,302 >> {'loss': 0.0230, 'learning_rate': 8.2717e-07, 'epoch': 3.66, 'throughput': 482.38}
530
-
531
- [INFO|callbacks.py:310] 2024-07-30 03:21:05,454 >> {'loss': 0.0106, 'learning_rate': 7.9500e-07, 'epoch': 3.69, 'throughput': 482.32}
532
-
533
- [INFO|callbacks.py:310] 2024-07-30 03:21:18,598 >> {'loss': 0.0238, 'learning_rate': 7.6335e-07, 'epoch': 3.72, 'throughput': 482.48}
534
-
535
- [INFO|callbacks.py:310] 2024-07-30 03:21:31,757 >> {'loss': 0.0088, 'learning_rate': 7.3223e-07, 'epoch': 3.74, 'throughput': 482.51}
536
-
537
- [INFO|callbacks.py:310] 2024-07-30 03:21:44,919 >> {'loss': 0.0391, 'learning_rate': 7.0165e-07, 'epoch': 3.77, 'throughput': 482.58}
538
-
539
- [INFO|callbacks.py:310] 2024-07-30 03:21:58,081 >> {'loss': 0.0008, 'learning_rate': 6.7162e-07, 'epoch': 3.79, 'throughput': 482.64}
540
-
541
- [INFO|callbacks.py:310] 2024-07-30 03:22:11,241 >> {'loss': 0.0177, 'learning_rate': 6.4214e-07, 'epoch': 3.82, 'throughput': 482.62}
542
-
543
- [INFO|callbacks.py:310] 2024-07-30 03:22:24,389 >> {'loss': 0.0001, 'learning_rate': 6.1323e-07, 'epoch': 3.85, 'throughput': 482.53}
544
-
545
- [INFO|callbacks.py:310] 2024-07-30 03:22:37,539 >> {'loss': 0.0002, 'learning_rate': 5.8489e-07, 'epoch': 3.87, 'throughput': 482.57}
546
-
547
- [INFO|callbacks.py:310] 2024-07-30 03:22:50,689 >> {'loss': 0.0044, 'learning_rate': 5.5714e-07, 'epoch': 3.90, 'throughput': 482.50}
548
-
549
- [INFO|callbacks.py:310] 2024-07-30 03:23:03,841 >> {'loss': 0.0015, 'learning_rate': 5.2997e-07, 'epoch': 3.92, 'throughput': 482.56}
550
-
551
- [INFO|callbacks.py:310] 2024-07-30 03:23:16,993 >> {'loss': 0.0003, 'learning_rate': 5.0341e-07, 'epoch': 3.95, 'throughput': 482.53}
552
-
553
- [INFO|callbacks.py:310] 2024-07-30 03:23:30,143 >> {'loss': 0.0361, 'learning_rate': 4.7746e-07, 'epoch': 3.97, 'throughput': 482.59}
554
-
555
- [INFO|callbacks.py:310] 2024-07-30 03:23:43,318 >> {'loss': 0.0005, 'learning_rate': 4.5212e-07, 'epoch': 4.00, 'throughput': 482.75}
556
-
557
- [INFO|callbacks.py:310] 2024-07-30 03:23:56,477 >> {'loss': 0.0022, 'learning_rate': 4.2741e-07, 'epoch': 4.03, 'throughput': 482.76}
558
-
559
- [INFO|callbacks.py:310] 2024-07-30 03:24:09,624 >> {'loss': 0.0212, 'learning_rate': 4.0332e-07, 'epoch': 4.05, 'throughput': 482.78}
560
-
561
- [INFO|callbacks.py:310] 2024-07-30 03:24:22,793 >> {'loss': 0.0003, 'learning_rate': 3.7988e-07, 'epoch': 4.08, 'throughput': 482.68}
562
-
563
- [INFO|callbacks.py:310] 2024-07-30 03:24:35,959 >> {'loss': 0.0047, 'learning_rate': 3.5708e-07, 'epoch': 4.10, 'throughput': 482.59}
564
-
565
- [INFO|callbacks.py:310] 2024-07-30 03:24:49,103 >> {'loss': 0.0014, 'learning_rate': 3.3494e-07, 'epoch': 4.13, 'throughput': 482.54}
566
-
567
- [INFO|callbacks.py:310] 2024-07-30 03:25:02,253 >> {'loss': 0.0006, 'learning_rate': 3.1345e-07, 'epoch': 4.15, 'throughput': 482.62}
568
-
569
- [INFO|callbacks.py:310] 2024-07-30 03:25:15,421 >> {'loss': 0.0003, 'learning_rate': 2.9263e-07, 'epoch': 4.18, 'throughput': 482.66}
570
-
571
- [INFO|callbacks.py:310] 2024-07-30 03:25:28,590 >> {'loss': 0.0021, 'learning_rate': 2.7248e-07, 'epoch': 4.21, 'throughput': 482.63}
572
-
573
- [INFO|callbacks.py:310] 2024-07-30 03:25:41,746 >> {'loss': 0.0001, 'learning_rate': 2.5301e-07, 'epoch': 4.23, 'throughput': 482.54}
574
-
575
- [INFO|callbacks.py:310] 2024-07-30 03:25:54,902 >> {'loss': 0.0007, 'learning_rate': 2.3423e-07, 'epoch': 4.26, 'throughput': 482.58}
576
-
577
- [INFO|callbacks.py:310] 2024-07-30 03:26:08,056 >> {'loss': 0.0013, 'learning_rate': 2.1614e-07, 'epoch': 4.28, 'throughput': 482.49}
578
-
579
- [INFO|callbacks.py:310] 2024-07-30 03:26:21,216 >> {'loss': 0.0002, 'learning_rate': 1.9874e-07, 'epoch': 4.31, 'throughput': 482.55}
580
-
581
- [INFO|callbacks.py:310] 2024-07-30 03:26:34,365 >> {'loss': 0.0011, 'learning_rate': 1.8204e-07, 'epoch': 4.34, 'throughput': 482.47}
582
-
583
- [INFO|callbacks.py:310] 2024-07-30 03:26:47,530 >> {'loss': 0.0001, 'learning_rate': 1.6605e-07, 'epoch': 4.36, 'throughput': 482.39}
584
-
585
- [INFO|callbacks.py:310] 2024-07-30 03:27:00,675 >> {'loss': 0.0006, 'learning_rate': 1.5077e-07, 'epoch': 4.39, 'throughput': 482.46}
586
-
587
- [INFO|callbacks.py:310] 2024-07-30 03:27:13,849 >> {'loss': 0.0003, 'learning_rate': 1.3620e-07, 'epoch': 4.41, 'throughput': 482.60}
588
-
589
- [INFO|callbacks.py:310] 2024-07-30 03:27:27,011 >> {'loss': 0.0002, 'learning_rate': 1.2236e-07, 'epoch': 4.44, 'throughput': 482.60}
590
-
591
- [INFO|callbacks.py:310] 2024-07-30 03:27:40,171 >> {'loss': 0.0027, 'learning_rate': 1.0924e-07, 'epoch': 4.46, 'throughput': 482.69}
592
-
593
- [INFO|callbacks.py:310] 2024-07-30 03:27:53,338 >> {'loss': 0.0002, 'learning_rate': 9.6846e-08, 'epoch': 4.49, 'throughput': 482.67}
594
-
595
- [INFO|callbacks.py:310] 2024-07-30 03:28:06,490 >> {'loss': 0.0001, 'learning_rate': 8.5185e-08, 'epoch': 4.52, 'throughput': 482.72}
596
-
597
- [INFO|callbacks.py:310] 2024-07-30 03:28:19,653 >> {'loss': 0.0109, 'learning_rate': 7.4261e-08, 'epoch': 4.54, 'throughput': 482.85}
598
-
599
- [INFO|callbacks.py:310] 2024-07-30 03:28:32,819 >> {'loss': 0.0039, 'learning_rate': 6.4075e-08, 'epoch': 4.57, 'throughput': 482.78}
600
-
601
- [INFO|callbacks.py:310] 2024-07-30 03:28:45,970 >> {'loss': 0.0026, 'learning_rate': 5.4631e-08, 'epoch': 4.59, 'throughput': 482.83}
602
-
603
- [INFO|callbacks.py:310] 2024-07-30 03:28:59,127 >> {'loss': 0.0002, 'learning_rate': 4.5932e-08, 'epoch': 4.62, 'throughput': 482.85}
604
-
605
- [INFO|callbacks.py:310] 2024-07-30 03:29:12,277 >> {'loss': 0.0044, 'learning_rate': 3.7981e-08, 'epoch': 4.65, 'throughput': 482.83}
606
-
607
- [INFO|callbacks.py:310] 2024-07-30 03:29:25,426 >> {'loss': 0.0001, 'learning_rate': 3.0779e-08, 'epoch': 4.67, 'throughput': 482.83}
608
-
609
- [INFO|callbacks.py:310] 2024-07-30 03:29:38,563 >> {'loss': 0.0103, 'learning_rate': 2.4330e-08, 'epoch': 4.70, 'throughput': 482.82}
610
 
611
- [INFO|callbacks.py:310] 2024-07-30 03:29:51,712 >> {'loss': 0.0002, 'learning_rate': 1.8635e-08, 'epoch': 4.72, 'throughput': 482.82}
612
 
613
- [INFO|callbacks.py:310] 2024-07-30 03:30:04,875 >> {'loss': 0.0038, 'learning_rate': 1.3695e-08, 'epoch': 4.75, 'throughput': 482.82}
 
614
 
615
- [INFO|callbacks.py:310] 2024-07-30 03:30:18,027 >> {'loss': 0.0039, 'learning_rate': 9.5133e-09, 'epoch': 4.77, 'throughput': 482.88}
616
 
617
- [INFO|callbacks.py:310] 2024-07-30 03:30:31,175 >> {'loss': 0.0005, 'learning_rate': 6.0899e-09, 'epoch': 4.80, 'throughput': 482.83}
618
 
619
- [INFO|callbacks.py:310] 2024-07-30 03:30:44,329 >> {'loss': 0.0002, 'learning_rate': 3.4262e-09, 'epoch': 4.83, 'throughput': 482.85}
620
 
621
- [INFO|callbacks.py:310] 2024-07-30 03:30:57,472 >> {'loss': 0.0011, 'learning_rate': 1.5229e-09, 'epoch': 4.85, 'throughput': 482.82}
622
 
623
- [INFO|callbacks.py:310] 2024-07-30 03:31:10,622 >> {'loss': 0.0007, 'learning_rate': 3.8076e-10, 'epoch': 4.88, 'throughput': 482.75}
624
 
625
- [INFO|callbacks.py:310] 2024-07-30 03:31:23,759 >> {'loss': 0.0002, 'learning_rate': 0.0000e+00, 'epoch': 4.90, 'throughput': 482.73}
626
 
627
- [INFO|trainer.py:3503] 2024-07-30 03:31:31,698 >> Saving model checkpoint to saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2/checkpoint-190
628
 
629
- [INFO|configuration_utils.py:472] 2024-07-30 03:31:31,701 >> Configuration saved in saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2/checkpoint-190/config.json
630
 
631
- [INFO|configuration_utils.py:807] 2024-07-30 03:31:31,701 >> Configuration saved in saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2/checkpoint-190/generation_config.json
632
 
633
- [INFO|modeling_utils.py:2763] 2024-07-30 03:31:48,048 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 4 checkpoint shards. You can find where each parameters has been saved in the index located at saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2/checkpoint-190/model.safetensors.index.json.
634
 
635
- [INFO|tokenization_utils_base.py:2702] 2024-07-30 03:31:48,052 >> tokenizer config file saved in saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2/checkpoint-190/tokenizer_config.json
636
 
637
- [INFO|tokenization_utils_base.py:2711] 2024-07-30 03:31:48,052 >> Special tokens file saved in saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2/checkpoint-190/special_tokens_map.json
638
 
639
- [INFO|trainer.py:2394] 2024-07-30 03:32:24,590 >>
640
 
641
- Training completed. Do not forget to share your model on huggingface.co/models =)
642
 
 
643
 
 
644
 
645
- [INFO|trainer.py:3503] 2024-07-30 03:32:32,434 >> Saving model checkpoint to saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2
646
 
647
- [INFO|configuration_utils.py:472] 2024-07-30 03:32:32,437 >> Configuration saved in saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2/config.json
648
 
649
- [INFO|configuration_utils.py:807] 2024-07-30 03:32:32,437 >> Configuration saved in saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2/generation_config.json
650
 
651
- [INFO|modeling_utils.py:2763] 2024-07-30 03:32:49,870 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 4 checkpoint shards. You can find where each parameters has been saved in the index located at saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2/model.safetensors.index.json.
652
 
653
- [INFO|tokenization_utils_base.py:2702] 2024-07-30 03:32:49,874 >> tokenizer config file saved in saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2/tokenizer_config.json
654
 
655
- [INFO|tokenization_utils_base.py:2711] 2024-07-30 03:32:49,874 >> Special tokens file saved in saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2/special_tokens_map.json
656
 
657
- [WARNING|ploting.py:89] 2024-07-30 03:32:51,207 >> No metric eval_loss to plot.
658
 
659
- [WARNING|ploting.py:89] 2024-07-30 03:32:51,207 >> No metric eval_accuracy to plot.
660
 
661
- [INFO|modelcard.py:449] 2024-07-30 03:32:51,207 >> Dropping the following result as it does not have all the necessary fields:
662
- {'task': {'name': 'Causal Language Modeling', 'type': 'text-generation'}}
663
 
 
1
+ 07/30/2024 03:45:41 - INFO - llamafactory.hparams.parser - Process rank: 1, device: cuda:1, n_gpu: 1, distributed training: True, compute dtype: None
2
 
3
+ 07/30/2024 03:45:41 - INFO - llamafactory.hparams.parser - Process rank: 2, device: cuda:2, n_gpu: 1, distributed training: True, compute dtype: None
4
 
5
+ 07/30/2024 03:45:41 - INFO - llamafactory.hparams.parser - Process rank: 3, device: cuda:3, n_gpu: 1, distributed training: True, compute dtype: None
6
 
7
+ 07/30/2024 03:45:41 - INFO - llamafactory.hparams.parser - Process rank: 4, device: cuda:4, n_gpu: 1, distributed training: True, compute dtype: None
8
 
9
+ 07/30/2024 03:45:41 - INFO - llamafactory.hparams.parser - Process rank: 6, device: cuda:6, n_gpu: 1, distributed training: True, compute dtype: None
10
 
11
+ [INFO|tokenization_utils_base.py:2287] 2024-07-30 03:45:41,182 >> loading file special_tokens_map.json
12
 
13
+ [INFO|tokenization_utils_base.py:2287] 2024-07-30 03:45:41,182 >> loading file tokenizer_config.json
14
 
15
+ [INFO|tokenization_utils_base.py:2533] 2024-07-30 03:45:41,444 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
16
 
17
+ [INFO|template.py:270] 2024-07-30 03:45:41,444 >> Replace eos token: <|eot_id|>
18
 
19
+ [INFO|loader.py:52] 2024-07-30 03:45:41,445 >> Loading dataset 0716_truthfulqa_benchmark_test_2.json...
20
 
21
+ 07/30/2024 03:45:41 - INFO - llamafactory.hparams.parser - Process rank: 7, device: cuda:7, n_gpu: 1, distributed training: True, compute dtype: None
22
 
23
+ 07/30/2024 03:45:41 - INFO - llamafactory.hparams.parser - Process rank: 5, device: cuda:5, n_gpu: 1, distributed training: True, compute dtype: None
24
 
25
+ 07/30/2024 03:45:41 - INFO - llamafactory.data.template - Replace eos token: <|eot_id|>
26
 
27
+ 07/30/2024 03:45:41 - INFO - llamafactory.data.template - Replace eos token: <|eot_id|>
28
 
29
+ 07/30/2024 03:45:41 - INFO - llamafactory.data.template - Replace eos token: <|eot_id|>
30
 
31
+ 07/30/2024 03:45:41 - INFO - llamafactory.data.template - Replace eos token: <|eot_id|>
32
 
33
+ 07/30/2024 03:45:41 - INFO - llamafactory.data.template - Replace eos token: <|eot_id|>
34
 
35
+ 07/30/2024 03:45:41 - INFO - llamafactory.data.template - Replace eos token: <|eot_id|>
36
 
37
+ 07/30/2024 03:45:41 - INFO - llamafactory.data.template - Replace eos token: <|eot_id|>
38
 
39
+ 07/30/2024 03:45:43 - INFO - llamafactory.data.loader - Loading dataset 0716_truthfulqa_benchmark_test_2.json...
40
 
41
+ 07/30/2024 03:45:43 - INFO - llamafactory.data.loader - Loading dataset 0716_truthfulqa_benchmark_test_2.json...
42
 
43
+ 07/30/2024 03:45:43 - INFO - llamafactory.data.loader - Loading dataset 0716_truthfulqa_benchmark_test_2.json...
44
 
45
+ 07/30/2024 03:45:43 - INFO - llamafactory.data.loader - Loading dataset 0716_truthfulqa_benchmark_test_2.json...
46
 
47
+ 07/30/2024 03:45:43 - INFO - llamafactory.data.loader - Loading dataset 0716_truthfulqa_benchmark_test_2.json...
48
 
49
+ 07/30/2024 03:45:43 - INFO - llamafactory.data.loader - Loading dataset 0716_truthfulqa_benchmark_test_2.json...
50
 
51
+ 07/30/2024 03:45:43 - INFO - llamafactory.data.loader - Loading dataset 0716_truthfulqa_benchmark_test_2.json...
52
 
53
+ [INFO|configuration_utils.py:731] 2024-07-30 03:45:46,553 >> loading configuration file saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2/config.json
54
 
55
+ [INFO|configuration_utils.py:800] 2024-07-30 03:45:46,554 >> Model config LlamaConfig {
56
+ "_name_or_path": "saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
57
  "architectures": [
58
  "LlamaForCausalLM"
59
  ],
 
88
  "tie_word_embeddings": false,
89
  "torch_dtype": "bfloat16",
90
  "transformers_version": "4.43.3",
91
+ "use_cache": false,
92
  "vocab_size": 128256
93
  }
94
 
95
 
96
+ [INFO|patcher.py:81] 2024-07-30 03:45:46,555 >> Using KV cache for faster generation.
97
+
98
+ [INFO|modeling_utils.py:3631] 2024-07-30 03:45:46,580 >> loading weights file saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2/model.safetensors.index.json
99
 
100
+ [INFO|modeling_utils.py:1572] 2024-07-30 03:45:46,580 >> Instantiating LlamaForCausalLM model under default dtype torch.bfloat16.
101
 
102
+ [INFO|configuration_utils.py:1038] 2024-07-30 03:45:46,582 >> Generate config GenerationConfig {
103
  "bos_token_id": 128000,
104
  "eos_token_id": [
105
  128001,
 
109
  }
110
 
111
 
112
+ 07/30/2024 03:45:46 - INFO - llamafactory.model.patcher - Using KV cache for faster generation.
113
+
114
+ 07/30/2024 03:45:46 - INFO - llamafactory.model.patcher - Using KV cache for faster generation.
115
+
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+ 07/30/2024 03:45:46 - INFO - llamafactory.model.patcher - Using KV cache for faster generation.
117
+
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+ 07/30/2024 03:45:46 - INFO - llamafactory.model.patcher - Using KV cache for faster generation.
119
+
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+ 07/30/2024 03:45:46 - INFO - llamafactory.model.patcher - Using KV cache for faster generation.
121
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+ 07/30/2024 03:45:46 - INFO - llamafactory.model.patcher - Using KV cache for faster generation.
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+ 07/30/2024 03:45:46 - INFO - llamafactory.model.patcher - Using KV cache for faster generation.
125
 
126
+ [INFO|modeling_utils.py:4463] 2024-07-30 03:45:50,818 >> All model checkpoint weights were used when initializing LlamaForCausalLM.
127
 
128
+
129
+ [INFO|modeling_utils.py:4471] 2024-07-30 03:45:50,818 >> All the weights of LlamaForCausalLM were initialized from the model checkpoint at saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2.
130
  If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training.
131
 
132
+ [INFO|configuration_utils.py:991] 2024-07-30 03:45:50,822 >> loading configuration file saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2/generation_config.json
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134
+ [INFO|configuration_utils.py:1038] 2024-07-30 03:45:50,822 >> Generate config GenerationConfig {
135
  "bos_token_id": 128000,
136
  "do_sample": true,
137
  "eos_token_id": [
 
144
  }
145
 
146
 
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+ [INFO|attention.py:84] 2024-07-30 03:45:50,828 >> Using torch SDPA for faster training and inference.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
148
 
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+ [INFO|loader.py:196] 2024-07-30 03:45:50,833 >> all params: 8,030,261,248
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+ [INFO|trainer.py:3819] 2024-07-30 03:45:50,942 >>
152
+ ***** Running Prediction *****
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154
+ [INFO|trainer.py:3821] 2024-07-30 03:45:50,942 >> Num examples = 1253
155
 
156
+ [INFO|trainer.py:3824] 2024-07-30 03:45:50,942 >> Batch size = 2
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158
+ [WARNING|logging.py:328] 2024-07-30 03:45:51,611 >> We detected that you are passing `past_key_values` as a tuple and this is deprecated and will be removed in v4.43. Please use an appropriate `Cache` class (https://huggingface.co/docs/transformers/v4.41.3/en/internal/generation_utils#transformers.Cache)
159
 
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+ 07/30/2024 03:45:52 - INFO - llamafactory.model.model_utils.attention - Using torch SDPA for faster training and inference.
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+ 07/30/2024 03:45:52 - INFO - llamafactory.model.model_utils.attention - Using torch SDPA for faster training and inference.
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+ 07/30/2024 03:45:52 - INFO - llamafactory.model.model_utils.attention - Using torch SDPA for faster training and inference.
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+ 07/30/2024 03:45:52 - INFO - llamafactory.model.loader - all params: 8,030,261,248
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+ 07/30/2024 03:45:52 - INFO - llamafactory.model.loader - all params: 8,030,261,248
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+ 07/30/2024 03:45:52 - INFO - llamafactory.model.loader - all params: 8,030,261,248
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+ 07/30/2024 03:45:52 - INFO - llamafactory.model.model_utils.attention - Using torch SDPA for faster training and inference.
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+ 07/30/2024 03:45:52 - INFO - llamafactory.model.model_utils.attention - Using torch SDPA for faster training and inference.
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+ 07/30/2024 03:45:52 - INFO - llamafactory.model.loader - all params: 8,030,261,248
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+ 07/30/2024 03:45:52 - INFO - llamafactory.model.loader - all params: 8,030,261,248
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+ 07/30/2024 03:45:52 - INFO - llamafactory.model.model_utils.attention - Using torch SDPA for faster training and inference.
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+ 07/30/2024 03:45:52 - INFO - llamafactory.model.loader - all params: 8,030,261,248
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+ 07/30/2024 03:45:52 - INFO - llamafactory.model.model_utils.attention - Using torch SDPA for faster training and inference.
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+ 07/30/2024 03:45:52 - INFO - llamafactory.model.loader - all params: 8,030,261,248
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+ 07/30/2024 03:45:52 - WARNING - transformers.models.llama.modeling_llama - We detected that you are passing `past_key_values` as a tuple and this is deprecated and will be removed in v4.43. Please use an appropriate `Cache` class (https://huggingface.co/docs/transformers/v4.41.3/en/internal/generation_utils#transformers.Cache)
189
 
190
+ 07/30/2024 03:45:52 - WARNING - transformers.models.llama.modeling_llama - We detected that you are passing `past_key_values` as a tuple and this is deprecated and will be removed in v4.43. Please use an appropriate `Cache` class (https://huggingface.co/docs/transformers/v4.41.3/en/internal/generation_utils#transformers.Cache)
191
 
192
+ 07/30/2024 03:45:52 - WARNING - transformers.models.llama.modeling_llama - We detected that you are passing `past_key_values` as a tuple and this is deprecated and will be removed in v4.43. Please use an appropriate `Cache` class (https://huggingface.co/docs/transformers/v4.41.3/en/internal/generation_utils#transformers.Cache)
193
 
194
+ 07/30/2024 03:45:52 - WARNING - transformers.models.llama.modeling_llama - We detected that you are passing `past_key_values` as a tuple and this is deprecated and will be removed in v4.43. Please use an appropriate `Cache` class (https://huggingface.co/docs/transformers/v4.41.3/en/internal/generation_utils#transformers.Cache)
195
 
196
+ 07/30/2024 03:45:52 - WARNING - transformers.models.llama.modeling_llama - We detected that you are passing `past_key_values` as a tuple and this is deprecated and will be removed in v4.43. Please use an appropriate `Cache` class (https://huggingface.co/docs/transformers/v4.41.3/en/internal/generation_utils#transformers.Cache)
197
 
198
+ 07/30/2024 03:45:52 - WARNING - transformers.models.llama.modeling_llama - We detected that you are passing `past_key_values` as a tuple and this is deprecated and will be removed in v4.43. Please use an appropriate `Cache` class (https://huggingface.co/docs/transformers/v4.41.3/en/internal/generation_utils#transformers.Cache)
199
 
200
+ 07/30/2024 03:45:52 - WARNING - transformers.models.llama.modeling_llama - We detected that you are passing `past_key_values` as a tuple and this is deprecated and will be removed in v4.43. Please use an appropriate `Cache` class (https://huggingface.co/docs/transformers/v4.41.3/en/internal/generation_utils#transformers.Cache)
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202
+ [INFO|trainer.py:127] 2024-07-30 03:45:59,801 >> Saving prediction results to saves/LLaMA3.1-8B-Chat/full/eval_2024-07-30-02-47-53_llama3.1_truthqa_bench2/generated_predictions.jsonl
 
203
 
trainer_log.jsonl CHANGED
@@ -1,191 +1,15 @@
1
- {"current_steps": 1, "total_steps": 190, "loss": 12.476, "learning_rate": 5.000000000000001e-07, "epoch": 0.025806451612903226, "percentage": 0.53, "elapsed_time": "0:00:14", "remaining_time": "0:45:58", "throughput": "439.53", "total_tokens": 6416}
2
- {"current_steps": 2, "total_steps": 190, "loss": 12.1047, "learning_rate": 1.0000000000000002e-06, "epoch": 0.05161290322580645, "percentage": 1.05, "elapsed_time": "0:00:27", "remaining_time": "0:43:30", "throughput": "467.79", "total_tokens": 12992}
3
- {"current_steps": 3, "total_steps": 190, "loss": 12.0404, "learning_rate": 1.5e-06, "epoch": 0.07741935483870968, "percentage": 1.58, "elapsed_time": "0:00:40", "remaining_time": "0:42:31", "throughput": "475.65", "total_tokens": 19472}
4
- {"current_steps": 4, "total_steps": 190, "loss": 10.5293, "learning_rate": 2.0000000000000003e-06, "epoch": 0.1032258064516129, "percentage": 2.11, "elapsed_time": "0:00:54", "remaining_time": "0:41:55", "throughput": "479.47", "total_tokens": 25936}
5
- {"current_steps": 5, "total_steps": 190, "loss": 8.3117, "learning_rate": 2.5e-06, "epoch": 0.12903225806451613, "percentage": 2.63, "elapsed_time": "0:01:07", "remaining_time": "0:41:29", "throughput": "479.70", "total_tokens": 32272}
6
- {"current_steps": 6, "total_steps": 190, "loss": 6.0338, "learning_rate": 3e-06, "epoch": 0.15483870967741936, "percentage": 3.16, "elapsed_time": "0:01:20", "remaining_time": "0:41:06", "throughput": "480.34", "total_tokens": 38640}
7
- {"current_steps": 7, "total_steps": 190, "loss": 4.8226, "learning_rate": 3.5e-06, "epoch": 0.18064516129032257, "percentage": 3.68, "elapsed_time": "0:01:33", "remaining_time": "0:40:47", "throughput": "480.63", "total_tokens": 44992}
8
- {"current_steps": 8, "total_steps": 190, "loss": 2.9485, "learning_rate": 4.000000000000001e-06, "epoch": 0.2064516129032258, "percentage": 4.21, "elapsed_time": "0:01:46", "remaining_time": "0:40:29", "throughput": "480.63", "total_tokens": 51328}
9
- {"current_steps": 9, "total_steps": 190, "loss": 0.9784, "learning_rate": 4.5e-06, "epoch": 0.23225806451612904, "percentage": 4.74, "elapsed_time": "0:01:59", "remaining_time": "0:40:12", "throughput": "478.52", "total_tokens": 57408}
10
- {"current_steps": 10, "total_steps": 190, "loss": 0.5759, "learning_rate": 5e-06, "epoch": 0.25806451612903225, "percentage": 5.26, "elapsed_time": "0:02:13", "remaining_time": "0:39:56", "throughput": "478.41", "total_tokens": 63696}
11
- {"current_steps": 11, "total_steps": 190, "loss": 1.1284, "learning_rate": 4.9996192378909785e-06, "epoch": 0.2838709677419355, "percentage": 5.79, "elapsed_time": "0:02:26", "remaining_time": "0:39:40", "throughput": "478.35", "total_tokens": 69984}
12
- {"current_steps": 12, "total_steps": 190, "loss": 1.1272, "learning_rate": 4.99847706754774e-06, "epoch": 0.3096774193548387, "percentage": 6.32, "elapsed_time": "0:02:39", "remaining_time": "0:39:25", "throughput": "479.03", "total_tokens": 76384}
13
- {"current_steps": 13, "total_steps": 190, "loss": 0.9501, "learning_rate": 4.9965738368864345e-06, "epoch": 0.33548387096774196, "percentage": 6.84, "elapsed_time": "0:02:52", "remaining_time": "0:39:10", "throughput": "479.08", "total_tokens": 82704}
14
- {"current_steps": 14, "total_steps": 190, "loss": 0.461, "learning_rate": 4.993910125649561e-06, "epoch": 0.36129032258064514, "percentage": 7.37, "elapsed_time": "0:03:05", "remaining_time": "0:38:55", "throughput": "478.92", "total_tokens": 88976}
15
- {"current_steps": 15, "total_steps": 190, "loss": 1.2016, "learning_rate": 4.990486745229364e-06, "epoch": 0.3870967741935484, "percentage": 7.89, "elapsed_time": "0:03:18", "remaining_time": "0:38:41", "throughput": "479.89", "total_tokens": 95472}
16
- {"current_steps": 16, "total_steps": 190, "loss": 0.331, "learning_rate": 4.986304738420684e-06, "epoch": 0.4129032258064516, "percentage": 8.42, "elapsed_time": "0:03:32", "remaining_time": "0:38:26", "throughput": "480.39", "total_tokens": 101904}
17
- {"current_steps": 17, "total_steps": 190, "loss": 0.3565, "learning_rate": 4.981365379103306e-06, "epoch": 0.43870967741935485, "percentage": 8.95, "elapsed_time": "0:03:45", "remaining_time": "0:38:12", "throughput": "480.60", "total_tokens": 108272}
18
- {"current_steps": 18, "total_steps": 190, "loss": 0.6088, "learning_rate": 4.975670171853926e-06, "epoch": 0.4645161290322581, "percentage": 9.47, "elapsed_time": "0:03:58", "remaining_time": "0:37:58", "throughput": "480.01", "total_tokens": 114464}
19
- {"current_steps": 19, "total_steps": 190, "loss": 0.2701, "learning_rate": 4.9692208514878445e-06, "epoch": 0.49032258064516127, "percentage": 10.0, "elapsed_time": "0:04:11", "remaining_time": "0:37:44", "throughput": "480.13", "total_tokens": 120816}
20
- {"current_steps": 20, "total_steps": 190, "loss": 0.7005, "learning_rate": 4.962019382530521e-06, "epoch": 0.5161290322580645, "percentage": 10.53, "elapsed_time": "0:04:24", "remaining_time": "0:37:30", "throughput": "480.07", "total_tokens": 127120}
21
- {"current_steps": 21, "total_steps": 190, "loss": 0.3424, "learning_rate": 4.9540679586191605e-06, "epoch": 0.5419354838709678, "percentage": 11.05, "elapsed_time": "0:04:37", "remaining_time": "0:37:17", "throughput": "481.03", "total_tokens": 133712}
22
- {"current_steps": 22, "total_steps": 190, "loss": 0.6274, "learning_rate": 4.9453690018345144e-06, "epoch": 0.567741935483871, "percentage": 11.58, "elapsed_time": "0:04:51", "remaining_time": "0:37:03", "throughput": "480.58", "total_tokens": 139904}
23
- {"current_steps": 23, "total_steps": 190, "loss": 0.4183, "learning_rate": 4.935925161963089e-06, "epoch": 0.5935483870967742, "percentage": 12.11, "elapsed_time": "0:05:04", "remaining_time": "0:36:49", "throughput": "480.64", "total_tokens": 146256}
24
- {"current_steps": 24, "total_steps": 190, "loss": 0.1517, "learning_rate": 4.925739315689991e-06, "epoch": 0.6193548387096774, "percentage": 12.63, "elapsed_time": "0:05:17", "remaining_time": "0:36:35", "throughput": "481.29", "total_tokens": 152784}
25
- {"current_steps": 25, "total_steps": 190, "loss": 0.1906, "learning_rate": 4.914814565722671e-06, "epoch": 0.6451612903225806, "percentage": 13.16, "elapsed_time": "0:05:30", "remaining_time": "0:36:22", "throughput": "480.85", "total_tokens": 158976}
26
- {"current_steps": 26, "total_steps": 190, "loss": 0.1537, "learning_rate": 4.903154239845798e-06, "epoch": 0.6709677419354839, "percentage": 13.68, "elapsed_time": "0:05:43", "remaining_time": "0:36:08", "throughput": "480.78", "total_tokens": 165280}
27
- {"current_steps": 27, "total_steps": 190, "loss": 0.1957, "learning_rate": 4.890761889907589e-06, "epoch": 0.6967741935483871, "percentage": 14.21, "elapsed_time": "0:05:56", "remaining_time": "0:35:54", "throughput": "481.34", "total_tokens": 171808}
28
- {"current_steps": 28, "total_steps": 190, "loss": 0.3026, "learning_rate": 4.8776412907378845e-06, "epoch": 0.7225806451612903, "percentage": 14.74, "elapsed_time": "0:06:10", "remaining_time": "0:35:41", "throughput": "481.25", "total_tokens": 178112}
29
- {"current_steps": 29, "total_steps": 190, "loss": 0.2031, "learning_rate": 4.863796438998293e-06, "epoch": 0.7483870967741936, "percentage": 15.26, "elapsed_time": "0:06:23", "remaining_time": "0:35:27", "throughput": "481.25", "total_tokens": 184448}
30
- {"current_steps": 30, "total_steps": 190, "loss": 0.1461, "learning_rate": 4.849231551964771e-06, "epoch": 0.7741935483870968, "percentage": 15.79, "elapsed_time": "0:06:36", "remaining_time": "0:35:14", "throughput": "481.53", "total_tokens": 190896}
31
- {"current_steps": 31, "total_steps": 190, "loss": 0.1873, "learning_rate": 4.833951066243004e-06, "epoch": 0.8, "percentage": 16.32, "elapsed_time": "0:06:49", "remaining_time": "0:35:00", "throughput": "481.00", "total_tokens": 197024}
32
- {"current_steps": 32, "total_steps": 190, "loss": 0.1388, "learning_rate": 4.817959636416969e-06, "epoch": 0.8258064516129032, "percentage": 16.84, "elapsed_time": "0:07:02", "remaining_time": "0:34:47", "throughput": "480.75", "total_tokens": 203248}
33
- {"current_steps": 33, "total_steps": 190, "loss": 0.1127, "learning_rate": 4.801262133631101e-06, "epoch": 0.8516129032258064, "percentage": 17.37, "elapsed_time": "0:07:15", "remaining_time": "0:34:34", "throughput": "481.16", "total_tokens": 209760}
34
- {"current_steps": 34, "total_steps": 190, "loss": 0.1243, "learning_rate": 4.783863644106502e-06, "epoch": 0.8774193548387097, "percentage": 17.89, "elapsed_time": "0:07:29", "remaining_time": "0:34:20", "throughput": "480.87", "total_tokens": 215968}
35
- {"current_steps": 35, "total_steps": 190, "loss": 0.0969, "learning_rate": 4.765769467591626e-06, "epoch": 0.9032258064516129, "percentage": 18.42, "elapsed_time": "0:07:42", "remaining_time": "0:34:07", "throughput": "480.63", "total_tokens": 222192}
36
- {"current_steps": 36, "total_steps": 190, "loss": 0.089, "learning_rate": 4.746985115747918e-06, "epoch": 0.9290322580645162, "percentage": 18.95, "elapsed_time": "0:07:55", "remaining_time": "0:33:53", "throughput": "480.62", "total_tokens": 228512}
37
- {"current_steps": 37, "total_steps": 190, "loss": 0.1703, "learning_rate": 4.72751631047092e-06, "epoch": 0.9548387096774194, "percentage": 19.47, "elapsed_time": "0:08:08", "remaining_time": "0:33:40", "throughput": "481.20", "total_tokens": 235120}
38
- {"current_steps": 38, "total_steps": 190, "loss": 0.1132, "learning_rate": 4.707368982147318e-06, "epoch": 0.9806451612903225, "percentage": 20.0, "elapsed_time": "0:08:21", "remaining_time": "0:33:27", "throughput": "481.46", "total_tokens": 241584}
39
- {"current_steps": 39, "total_steps": 190, "loss": 0.1294, "learning_rate": 4.68654926784849e-06, "epoch": 1.0064516129032257, "percentage": 20.53, "elapsed_time": "0:08:34", "remaining_time": "0:33:13", "throughput": "481.77", "total_tokens": 248080}
40
- {"current_steps": 40, "total_steps": 190, "loss": 0.0881, "learning_rate": 4.665063509461098e-06, "epoch": 1.032258064516129, "percentage": 21.05, "elapsed_time": "0:08:48", "remaining_time": "0:33:00", "throughput": "481.78", "total_tokens": 254416}
41
- {"current_steps": 41, "total_steps": 190, "loss": 0.0504, "learning_rate": 4.642918251755281e-06, "epoch": 1.0580645161290323, "percentage": 21.58, "elapsed_time": "0:09:01", "remaining_time": "0:32:46", "throughput": "481.55", "total_tokens": 260640}
42
- {"current_steps": 42, "total_steps": 190, "loss": 0.0723, "learning_rate": 4.620120240391065e-06, "epoch": 1.0838709677419356, "percentage": 22.11, "elapsed_time": "0:09:14", "remaining_time": "0:32:33", "throughput": "481.72", "total_tokens": 267072}
43
- {"current_steps": 43, "total_steps": 190, "loss": 0.0726, "learning_rate": 4.596676419863561e-06, "epoch": 1.1096774193548387, "percentage": 22.63, "elapsed_time": "0:09:27", "remaining_time": "0:32:20", "throughput": "481.69", "total_tokens": 273392}
44
- {"current_steps": 44, "total_steps": 190, "loss": 0.1355, "learning_rate": 4.572593931387604e-06, "epoch": 1.135483870967742, "percentage": 23.16, "elapsed_time": "0:09:40", "remaining_time": "0:32:06", "throughput": "481.60", "total_tokens": 279680}
45
- {"current_steps": 45, "total_steps": 190, "loss": 0.0713, "learning_rate": 4.54788011072248e-06, "epoch": 1.1612903225806452, "percentage": 23.68, "elapsed_time": "0:09:53", "remaining_time": "0:31:53", "throughput": "481.51", "total_tokens": 285968}
46
- {"current_steps": 46, "total_steps": 190, "loss": 0.0796, "learning_rate": 4.522542485937369e-06, "epoch": 1.1870967741935483, "percentage": 24.21, "elapsed_time": "0:10:07", "remaining_time": "0:31:40", "throughput": "481.50", "total_tokens": 292304}
47
- {"current_steps": 47, "total_steps": 190, "loss": 0.0778, "learning_rate": 4.496588775118232e-06, "epoch": 1.2129032258064516, "percentage": 24.74, "elapsed_time": "0:10:20", "remaining_time": "0:31:27", "throughput": "481.46", "total_tokens": 298608}
48
- {"current_steps": 48, "total_steps": 190, "loss": 0.0606, "learning_rate": 4.470026884016805e-06, "epoch": 1.238709677419355, "percentage": 25.26, "elapsed_time": "0:10:33", "remaining_time": "0:31:13", "throughput": "481.40", "total_tokens": 304912}
49
- {"current_steps": 49, "total_steps": 190, "loss": 0.0411, "learning_rate": 4.442864903642428e-06, "epoch": 1.2645161290322582, "percentage": 25.79, "elapsed_time": "0:10:46", "remaining_time": "0:31:00", "throughput": "481.53", "total_tokens": 311328}
50
- {"current_steps": 50, "total_steps": 190, "loss": 0.0773, "learning_rate": 4.415111107797445e-06, "epoch": 1.2903225806451613, "percentage": 26.32, "elapsed_time": "0:10:59", "remaining_time": "0:30:47", "throughput": "481.53", "total_tokens": 317664}
51
- {"current_steps": 51, "total_steps": 190, "loss": 0.0355, "learning_rate": 4.386773950556931e-06, "epoch": 1.3161290322580645, "percentage": 26.84, "elapsed_time": "0:11:12", "remaining_time": "0:30:33", "throughput": "481.73", "total_tokens": 324128}
52
- {"current_steps": 52, "total_steps": 190, "loss": 0.0607, "learning_rate": 4.357862063693486e-06, "epoch": 1.3419354838709676, "percentage": 27.37, "elapsed_time": "0:11:26", "remaining_time": "0:30:20", "throughput": "481.48", "total_tokens": 330304}
53
- {"current_steps": 53, "total_steps": 190, "loss": 0.0542, "learning_rate": 4.328384254047927e-06, "epoch": 1.367741935483871, "percentage": 27.89, "elapsed_time": "0:11:39", "remaining_time": "0:30:07", "throughput": "481.43", "total_tokens": 336608}
54
- {"current_steps": 54, "total_steps": 190, "loss": 0.0629, "learning_rate": 4.2983495008466285e-06, "epoch": 1.3935483870967742, "percentage": 28.42, "elapsed_time": "0:11:52", "remaining_time": "0:29:54", "throughput": "481.42", "total_tokens": 342944}
55
- {"current_steps": 55, "total_steps": 190, "loss": 0.0519, "learning_rate": 4.267766952966369e-06, "epoch": 1.4193548387096775, "percentage": 28.95, "elapsed_time": "0:12:05", "remaining_time": "0:29:40", "throughput": "481.73", "total_tokens": 349504}
56
- {"current_steps": 56, "total_steps": 190, "loss": 0.0481, "learning_rate": 4.236645926147493e-06, "epoch": 1.4451612903225808, "percentage": 29.47, "elapsed_time": "0:12:18", "remaining_time": "0:29:27", "throughput": "481.67", "total_tokens": 355808}
57
- {"current_steps": 57, "total_steps": 190, "loss": 0.0659, "learning_rate": 4.204995900156247e-06, "epoch": 1.4709677419354839, "percentage": 30.0, "elapsed_time": "0:12:31", "remaining_time": "0:29:14", "throughput": "481.67", "total_tokens": 362144}
58
- {"current_steps": 58, "total_steps": 190, "loss": 0.098, "learning_rate": 4.172826515897146e-06, "epoch": 1.4967741935483871, "percentage": 30.53, "elapsed_time": "0:12:45", "remaining_time": "0:29:01", "throughput": "482.09", "total_tokens": 368800}
59
- {"current_steps": 59, "total_steps": 190, "loss": 0.0411, "learning_rate": 4.140147572476269e-06, "epoch": 1.5225806451612902, "percentage": 31.05, "elapsed_time": "0:12:58", "remaining_time": "0:28:47", "throughput": "482.24", "total_tokens": 375264}
60
- {"current_steps": 60, "total_steps": 190, "loss": 0.0396, "learning_rate": 4.106969024216348e-06, "epoch": 1.5483870967741935, "percentage": 31.58, "elapsed_time": "0:13:11", "remaining_time": "0:28:34", "throughput": "481.97", "total_tokens": 381408}
61
- {"current_steps": 61, "total_steps": 190, "loss": 0.0413, "learning_rate": 4.073300977624594e-06, "epoch": 1.5741935483870968, "percentage": 32.11, "elapsed_time": "0:13:24", "remaining_time": "0:28:21", "throughput": "481.73", "total_tokens": 387552}
62
- {"current_steps": 62, "total_steps": 190, "loss": 0.1195, "learning_rate": 4.039153688314146e-06, "epoch": 1.6, "percentage": 32.63, "elapsed_time": "0:13:37", "remaining_time": "0:28:08", "throughput": "482.02", "total_tokens": 394128}
63
- {"current_steps": 63, "total_steps": 190, "loss": 0.0534, "learning_rate": 4.0045375578801216e-06, "epoch": 1.6258064516129034, "percentage": 33.16, "elapsed_time": "0:13:50", "remaining_time": "0:27:54", "throughput": "482.06", "total_tokens": 400512}
64
- {"current_steps": 64, "total_steps": 190, "loss": 0.0662, "learning_rate": 3.969463130731183e-06, "epoch": 1.6516129032258065, "percentage": 33.68, "elapsed_time": "0:14:04", "remaining_time": "0:27:41", "throughput": "481.93", "total_tokens": 406752}
65
- {"current_steps": 65, "total_steps": 190, "loss": 0.0462, "learning_rate": 3.933941090877615e-06, "epoch": 1.6774193548387095, "percentage": 34.21, "elapsed_time": "0:14:17", "remaining_time": "0:27:28", "throughput": "481.86", "total_tokens": 413040}
66
- {"current_steps": 66, "total_steps": 190, "loss": 0.0899, "learning_rate": 3.897982258676867e-06, "epoch": 1.7032258064516128, "percentage": 34.74, "elapsed_time": "0:14:30", "remaining_time": "0:27:15", "throughput": "481.90", "total_tokens": 419408}
67
- {"current_steps": 67, "total_steps": 190, "loss": 0.0691, "learning_rate": 3.861597587537568e-06, "epoch": 1.729032258064516, "percentage": 35.26, "elapsed_time": "0:14:43", "remaining_time": "0:27:01", "throughput": "482.08", "total_tokens": 425920}
68
- {"current_steps": 68, "total_steps": 190, "loss": 0.1022, "learning_rate": 3.824798160583012e-06, "epoch": 1.7548387096774194, "percentage": 35.79, "elapsed_time": "0:14:56", "remaining_time": "0:26:48", "throughput": "482.24", "total_tokens": 432400}
69
- {"current_steps": 69, "total_steps": 190, "loss": 0.1062, "learning_rate": 3.787595187275136e-06, "epoch": 1.7806451612903227, "percentage": 36.32, "elapsed_time": "0:15:09", "remaining_time": "0:26:35", "throughput": "482.17", "total_tokens": 438688}
70
- {"current_steps": 70, "total_steps": 190, "loss": 0.0491, "learning_rate": 3.7500000000000005e-06, "epoch": 1.8064516129032258, "percentage": 36.84, "elapsed_time": "0:15:22", "remaining_time": "0:26:22", "throughput": "482.44", "total_tokens": 445280}
71
- {"current_steps": 71, "total_steps": 190, "loss": 0.1507, "learning_rate": 3.7120240506158433e-06, "epoch": 1.832258064516129, "percentage": 37.37, "elapsed_time": "0:15:36", "remaining_time": "0:26:09", "throughput": "482.42", "total_tokens": 451616}
72
- {"current_steps": 72, "total_steps": 190, "loss": 0.1234, "learning_rate": 3.6736789069647273e-06, "epoch": 1.8580645161290321, "percentage": 37.89, "elapsed_time": "0:15:49", "remaining_time": "0:25:55", "throughput": "482.31", "total_tokens": 457856}
73
- {"current_steps": 73, "total_steps": 190, "loss": 0.045, "learning_rate": 3.634976249348867e-06, "epoch": 1.8838709677419354, "percentage": 38.42, "elapsed_time": "0:16:02", "remaining_time": "0:25:42", "throughput": "482.26", "total_tokens": 464144}
74
- {"current_steps": 74, "total_steps": 190, "loss": 0.0615, "learning_rate": 3.595927866972694e-06, "epoch": 1.9096774193548387, "percentage": 38.95, "elapsed_time": "0:16:15", "remaining_time": "0:25:29", "throughput": "482.50", "total_tokens": 470736}
75
- {"current_steps": 75, "total_steps": 190, "loss": 0.1961, "learning_rate": 3.556545654351749e-06, "epoch": 1.935483870967742, "percentage": 39.47, "elapsed_time": "0:16:28", "remaining_time": "0:25:16", "throughput": "482.59", "total_tokens": 477168}
76
- {"current_steps": 76, "total_steps": 190, "loss": 0.2311, "learning_rate": 3.516841607689501e-06, "epoch": 1.9612903225806453, "percentage": 40.0, "elapsed_time": "0:16:41", "remaining_time": "0:25:02", "throughput": "482.60", "total_tokens": 483536}
77
- {"current_steps": 77, "total_steps": 190, "loss": 0.1556, "learning_rate": 3.476827821223184e-06, "epoch": 1.9870967741935484, "percentage": 40.53, "elapsed_time": "0:16:55", "remaining_time": "0:24:49", "throughput": "482.48", "total_tokens": 489760}
78
- {"current_steps": 78, "total_steps": 190, "loss": 0.0626, "learning_rate": 3.436516483539781e-06, "epoch": 2.0129032258064514, "percentage": 41.05, "elapsed_time": "0:17:08", "remaining_time": "0:24:36", "throughput": "482.38", "total_tokens": 496000}
79
- {"current_steps": 79, "total_steps": 190, "loss": 0.0197, "learning_rate": 3.39591987386325e-06, "epoch": 2.0387096774193547, "percentage": 41.58, "elapsed_time": "0:17:21", "remaining_time": "0:24:23", "throughput": "482.41", "total_tokens": 502384}
80
- {"current_steps": 80, "total_steps": 190, "loss": 0.0057, "learning_rate": 3.3550503583141726e-06, "epoch": 2.064516129032258, "percentage": 42.11, "elapsed_time": "0:17:34", "remaining_time": "0:24:10", "throughput": "482.65", "total_tokens": 508992}
81
- {"current_steps": 81, "total_steps": 190, "loss": 0.029, "learning_rate": 3.313920386142892e-06, "epoch": 2.0903225806451613, "percentage": 42.63, "elapsed_time": "0:17:47", "remaining_time": "0:23:56", "throughput": "482.53", "total_tokens": 515216}
82
- {"current_steps": 82, "total_steps": 190, "loss": 0.0593, "learning_rate": 3.272542485937369e-06, "epoch": 2.1161290322580646, "percentage": 43.16, "elapsed_time": "0:18:00", "remaining_time": "0:23:43", "throughput": "482.74", "total_tokens": 521792}
83
- {"current_steps": 83, "total_steps": 190, "loss": 0.0455, "learning_rate": 3.230929261806842e-06, "epoch": 2.141935483870968, "percentage": 43.68, "elapsed_time": "0:18:14", "remaining_time": "0:23:30", "throughput": "482.77", "total_tokens": 528176}
84
- {"current_steps": 84, "total_steps": 190, "loss": 0.0325, "learning_rate": 3.189093389542498e-06, "epoch": 2.167741935483871, "percentage": 44.21, "elapsed_time": "0:18:27", "remaining_time": "0:23:17", "throughput": "482.74", "total_tokens": 534496}
85
- {"current_steps": 85, "total_steps": 190, "loss": 0.0071, "learning_rate": 3.147047612756302e-06, "epoch": 2.193548387096774, "percentage": 44.74, "elapsed_time": "0:18:40", "remaining_time": "0:23:03", "throughput": "482.90", "total_tokens": 541024}
86
- {"current_steps": 86, "total_steps": 190, "loss": 0.0336, "learning_rate": 3.1048047389991693e-06, "epoch": 2.2193548387096773, "percentage": 45.26, "elapsed_time": "0:18:53", "remaining_time": "0:22:50", "throughput": "482.86", "total_tokens": 547328}
87
- {"current_steps": 87, "total_steps": 190, "loss": 0.0389, "learning_rate": 3.062377635859663e-06, "epoch": 2.2451612903225806, "percentage": 45.79, "elapsed_time": "0:19:06", "remaining_time": "0:22:37", "throughput": "482.92", "total_tokens": 553760}
88
- {"current_steps": 88, "total_steps": 190, "loss": 0.0016, "learning_rate": 3.019779227044398e-06, "epoch": 2.270967741935484, "percentage": 46.32, "elapsed_time": "0:19:19", "remaining_time": "0:22:24", "throughput": "482.87", "total_tokens": 560048}
89
- {"current_steps": 89, "total_steps": 190, "loss": 0.0625, "learning_rate": 2.9770224884413625e-06, "epoch": 2.296774193548387, "percentage": 46.84, "elapsed_time": "0:19:33", "remaining_time": "0:22:11", "throughput": "483.05", "total_tokens": 566624}
90
- {"current_steps": 90, "total_steps": 190, "loss": 0.0201, "learning_rate": 2.9341204441673267e-06, "epoch": 2.3225806451612905, "percentage": 47.37, "elapsed_time": "0:19:46", "remaining_time": "0:21:57", "throughput": "482.95", "total_tokens": 572864}
91
- {"current_steps": 91, "total_steps": 190, "loss": 0.0126, "learning_rate": 2.8910861626005774e-06, "epoch": 2.3483870967741938, "percentage": 47.89, "elapsed_time": "0:19:59", "remaining_time": "0:21:44", "throughput": "482.79", "total_tokens": 579024}
92
- {"current_steps": 92, "total_steps": 190, "loss": 0.0148, "learning_rate": 2.847932752400164e-06, "epoch": 2.3741935483870966, "percentage": 48.42, "elapsed_time": "0:20:12", "remaining_time": "0:21:31", "throughput": "482.91", "total_tokens": 585536}
93
- {"current_steps": 93, "total_steps": 190, "loss": 0.014, "learning_rate": 2.804673358512869e-06, "epoch": 2.4, "percentage": 48.95, "elapsed_time": "0:20:25", "remaining_time": "0:21:18", "throughput": "482.83", "total_tokens": 591792}
94
- {"current_steps": 94, "total_steps": 190, "loss": 0.0096, "learning_rate": 2.761321158169134e-06, "epoch": 2.425806451612903, "percentage": 49.47, "elapsed_time": "0:20:38", "remaining_time": "0:21:05", "throughput": "482.82", "total_tokens": 598144}
95
- {"current_steps": 95, "total_steps": 190, "loss": 0.0249, "learning_rate": 2.717889356869146e-06, "epoch": 2.4516129032258065, "percentage": 50.0, "elapsed_time": "0:20:52", "remaining_time": "0:20:52", "throughput": "482.82", "total_tokens": 604496}
96
- {"current_steps": 96, "total_steps": 190, "loss": 0.0358, "learning_rate": 2.6743911843603134e-06, "epoch": 2.47741935483871, "percentage": 50.53, "elapsed_time": "0:21:05", "remaining_time": "0:20:38", "throughput": "482.76", "total_tokens": 610784}
97
- {"current_steps": 97, "total_steps": 190, "loss": 0.0494, "learning_rate": 2.6308398906073603e-06, "epoch": 2.5032258064516126, "percentage": 51.05, "elapsed_time": "0:21:18", "remaining_time": "0:20:25", "throughput": "482.67", "total_tokens": 617024}
98
- {"current_steps": 98, "total_steps": 190, "loss": 0.0092, "learning_rate": 2.587248741756253e-06, "epoch": 2.5290322580645164, "percentage": 51.58, "elapsed_time": "0:21:31", "remaining_time": "0:20:12", "throughput": "482.63", "total_tokens": 623312}
99
- {"current_steps": 99, "total_steps": 190, "loss": 0.0215, "learning_rate": 2.543631016093209e-06, "epoch": 2.554838709677419, "percentage": 52.11, "elapsed_time": "0:21:44", "remaining_time": "0:19:59", "throughput": "482.59", "total_tokens": 629616}
100
- {"current_steps": 100, "total_steps": 190, "loss": 0.0122, "learning_rate": 2.5e-06, "epoch": 2.5806451612903225, "percentage": 52.63, "elapsed_time": "0:21:57", "remaining_time": "0:19:46", "throughput": "482.73", "total_tokens": 636144}
101
- {"current_steps": 101, "total_steps": 190, "loss": 0.0296, "learning_rate": 2.4563689839067913e-06, "epoch": 2.606451612903226, "percentage": 53.16, "elapsed_time": "0:22:10", "remaining_time": "0:19:32", "throughput": "482.73", "total_tokens": 642496}
102
- {"current_steps": 102, "total_steps": 190, "loss": 0.0089, "learning_rate": 2.4127512582437486e-06, "epoch": 2.632258064516129, "percentage": 53.68, "elapsed_time": "0:22:24", "remaining_time": "0:19:19", "throughput": "482.78", "total_tokens": 648912}
103
- {"current_steps": 103, "total_steps": 190, "loss": 0.0406, "learning_rate": 2.3691601093926406e-06, "epoch": 2.6580645161290324, "percentage": 54.21, "elapsed_time": "0:22:37", "remaining_time": "0:19:06", "throughput": "482.65", "total_tokens": 655088}
104
- {"current_steps": 104, "total_steps": 190, "loss": 0.0114, "learning_rate": 2.325608815639687e-06, "epoch": 2.6838709677419352, "percentage": 54.74, "elapsed_time": "0:22:50", "remaining_time": "0:18:53", "throughput": "482.82", "total_tokens": 661680}
105
- {"current_steps": 105, "total_steps": 190, "loss": 0.0396, "learning_rate": 2.2821106431308546e-06, "epoch": 2.709677419354839, "percentage": 55.26, "elapsed_time": "0:23:03", "remaining_time": "0:18:40", "throughput": "482.81", "total_tokens": 668016}
106
- {"current_steps": 106, "total_steps": 190, "loss": 0.0077, "learning_rate": 2.238678841830867e-06, "epoch": 2.735483870967742, "percentage": 55.79, "elapsed_time": "0:23:16", "remaining_time": "0:18:26", "throughput": "482.67", "total_tokens": 674176}
107
- {"current_steps": 107, "total_steps": 190, "loss": 0.0044, "learning_rate": 2.195326641487132e-06, "epoch": 2.761290322580645, "percentage": 56.32, "elapsed_time": "0:23:29", "remaining_time": "0:18:13", "throughput": "482.63", "total_tokens": 680464}
108
- {"current_steps": 108, "total_steps": 190, "loss": 0.0045, "learning_rate": 2.1520672475998374e-06, "epoch": 2.7870967741935484, "percentage": 56.84, "elapsed_time": "0:23:43", "remaining_time": "0:18:00", "throughput": "482.54", "total_tokens": 686688}
109
- {"current_steps": 109, "total_steps": 190, "loss": 0.0405, "learning_rate": 2.1089138373994226e-06, "epoch": 2.8129032258064517, "percentage": 57.37, "elapsed_time": "0:23:56", "remaining_time": "0:17:47", "throughput": "482.51", "total_tokens": 692992}
110
- {"current_steps": 110, "total_steps": 190, "loss": 0.0225, "learning_rate": 2.0658795558326745e-06, "epoch": 2.838709677419355, "percentage": 57.89, "elapsed_time": "0:24:09", "remaining_time": "0:17:34", "throughput": "482.55", "total_tokens": 699392}
111
- {"current_steps": 111, "total_steps": 190, "loss": 0.0415, "learning_rate": 2.022977511558638e-06, "epoch": 2.864516129032258, "percentage": 58.42, "elapsed_time": "0:24:22", "remaining_time": "0:17:20", "throughput": "482.50", "total_tokens": 705680}
112
- {"current_steps": 112, "total_steps": 190, "loss": 0.0173, "learning_rate": 1.9802207729556023e-06, "epoch": 2.8903225806451616, "percentage": 58.95, "elapsed_time": "0:24:35", "remaining_time": "0:17:07", "throughput": "482.45", "total_tokens": 711952}
113
- {"current_steps": 113, "total_steps": 190, "loss": 0.0005, "learning_rate": 1.937622364140338e-06, "epoch": 2.9161290322580644, "percentage": 59.47, "elapsed_time": "0:24:48", "remaining_time": "0:16:54", "throughput": "482.38", "total_tokens": 718192}
114
- {"current_steps": 114, "total_steps": 190, "loss": 0.0306, "learning_rate": 1.895195261000831e-06, "epoch": 2.9419354838709677, "percentage": 60.0, "elapsed_time": "0:25:02", "remaining_time": "0:16:41", "throughput": "482.57", "total_tokens": 724832}
115
- {"current_steps": 115, "total_steps": 190, "loss": 0.0422, "learning_rate": 1.852952387243698e-06, "epoch": 2.967741935483871, "percentage": 60.53, "elapsed_time": "0:25:15", "remaining_time": "0:16:28", "throughput": "482.66", "total_tokens": 731312}
116
- {"current_steps": 116, "total_steps": 190, "loss": 0.0472, "learning_rate": 1.8109066104575023e-06, "epoch": 2.9935483870967743, "percentage": 61.05, "elapsed_time": "0:25:28", "remaining_time": "0:16:14", "throughput": "482.55", "total_tokens": 737488}
117
- {"current_steps": 117, "total_steps": 190, "loss": 0.0259, "learning_rate": 1.7690707381931585e-06, "epoch": 3.0193548387096776, "percentage": 61.58, "elapsed_time": "0:25:41", "remaining_time": "0:16:01", "throughput": "482.50", "total_tokens": 743760}
118
- {"current_steps": 118, "total_steps": 190, "loss": 0.0029, "learning_rate": 1.7274575140626318e-06, "epoch": 3.0451612903225804, "percentage": 62.11, "elapsed_time": "0:25:54", "remaining_time": "0:15:48", "throughput": "482.46", "total_tokens": 750048}
119
- {"current_steps": 119, "total_steps": 190, "loss": 0.035, "learning_rate": 1.686079613857109e-06, "epoch": 3.0709677419354837, "percentage": 62.63, "elapsed_time": "0:26:07", "remaining_time": "0:15:35", "throughput": "482.46", "total_tokens": 756400}
120
- {"current_steps": 120, "total_steps": 190, "loss": 0.0015, "learning_rate": 1.6449496416858285e-06, "epoch": 3.096774193548387, "percentage": 63.16, "elapsed_time": "0:26:20", "remaining_time": "0:15:22", "throughput": "482.26", "total_tokens": 762432}
121
- {"current_steps": 121, "total_steps": 190, "loss": 0.0006, "learning_rate": 1.6040801261367494e-06, "epoch": 3.1225806451612903, "percentage": 63.68, "elapsed_time": "0:26:34", "remaining_time": "0:15:09", "throughput": "482.20", "total_tokens": 768688}
122
- {"current_steps": 122, "total_steps": 190, "loss": 0.0143, "learning_rate": 1.56348351646022e-06, "epoch": 3.1483870967741936, "percentage": 64.21, "elapsed_time": "0:26:47", "remaining_time": "0:14:55", "throughput": "482.19", "total_tokens": 775024}
123
- {"current_steps": 123, "total_steps": 190, "loss": 0.0219, "learning_rate": 1.5231721787768162e-06, "epoch": 3.174193548387097, "percentage": 64.74, "elapsed_time": "0:27:00", "remaining_time": "0:14:42", "throughput": "482.19", "total_tokens": 781360}
124
- {"current_steps": 124, "total_steps": 190, "loss": 0.0074, "learning_rate": 1.4831583923105e-06, "epoch": 3.2, "percentage": 65.26, "elapsed_time": "0:27:13", "remaining_time": "0:14:29", "throughput": "482.31", "total_tokens": 787888}
125
- {"current_steps": 125, "total_steps": 190, "loss": 0.0052, "learning_rate": 1.443454345648252e-06, "epoch": 3.225806451612903, "percentage": 65.79, "elapsed_time": "0:27:26", "remaining_time": "0:14:16", "throughput": "482.23", "total_tokens": 794112}
126
- {"current_steps": 126, "total_steps": 190, "loss": 0.0013, "learning_rate": 1.4040721330273063e-06, "epoch": 3.2516129032258063, "percentage": 66.32, "elapsed_time": "0:27:39", "remaining_time": "0:14:03", "throughput": "482.19", "total_tokens": 800384}
127
- {"current_steps": 127, "total_steps": 190, "loss": 0.0018, "learning_rate": 1.3650237506511333e-06, "epoch": 3.2774193548387096, "percentage": 66.84, "elapsed_time": "0:27:53", "remaining_time": "0:13:49", "throughput": "482.26", "total_tokens": 806848}
128
- {"current_steps": 128, "total_steps": 190, "loss": 0.0077, "learning_rate": 1.3263210930352737e-06, "epoch": 3.303225806451613, "percentage": 67.37, "elapsed_time": "0:28:06", "remaining_time": "0:13:36", "throughput": "482.22", "total_tokens": 813136}
129
- {"current_steps": 129, "total_steps": 190, "loss": 0.0138, "learning_rate": 1.2879759493841577e-06, "epoch": 3.329032258064516, "percentage": 67.89, "elapsed_time": "0:28:19", "remaining_time": "0:13:23", "throughput": "482.24", "total_tokens": 819504}
130
- {"current_steps": 130, "total_steps": 190, "loss": 0.0102, "learning_rate": 1.2500000000000007e-06, "epoch": 3.3548387096774195, "percentage": 68.42, "elapsed_time": "0:28:32", "remaining_time": "0:13:10", "throughput": "482.29", "total_tokens": 825936}
131
- {"current_steps": 131, "total_steps": 190, "loss": 0.0067, "learning_rate": 1.2124048127248644e-06, "epoch": 3.3806451612903228, "percentage": 68.95, "elapsed_time": "0:28:45", "remaining_time": "0:12:57", "throughput": "482.41", "total_tokens": 832496}
132
- {"current_steps": 132, "total_steps": 190, "loss": 0.0056, "learning_rate": 1.1752018394169882e-06, "epoch": 3.4064516129032256, "percentage": 69.47, "elapsed_time": "0:28:58", "remaining_time": "0:12:44", "throughput": "482.43", "total_tokens": 838864}
133
- {"current_steps": 133, "total_steps": 190, "loss": 0.0066, "learning_rate": 1.1384024124624324e-06, "epoch": 3.432258064516129, "percentage": 70.0, "elapsed_time": "0:29:12", "remaining_time": "0:12:30", "throughput": "482.59", "total_tokens": 845504}
134
- {"current_steps": 134, "total_steps": 190, "loss": 0.0033, "learning_rate": 1.1020177413231334e-06, "epoch": 3.458064516129032, "percentage": 70.53, "elapsed_time": "0:29:25", "remaining_time": "0:12:17", "throughput": "482.61", "total_tokens": 851888}
135
- {"current_steps": 135, "total_steps": 190, "loss": 0.0008, "learning_rate": 1.0660589091223854e-06, "epoch": 3.4838709677419355, "percentage": 71.05, "elapsed_time": "0:29:38", "remaining_time": "0:12:04", "throughput": "482.56", "total_tokens": 858144}
136
- {"current_steps": 136, "total_steps": 190, "loss": 0.0027, "learning_rate": 1.0305368692688175e-06, "epoch": 3.509677419354839, "percentage": 71.58, "elapsed_time": "0:29:51", "remaining_time": "0:11:51", "throughput": "482.56", "total_tokens": 864496}
137
- {"current_steps": 137, "total_steps": 190, "loss": 0.0021, "learning_rate": 9.95462442119879e-07, "epoch": 3.535483870967742, "percentage": 72.11, "elapsed_time": "0:30:04", "remaining_time": "0:11:38", "throughput": "482.46", "total_tokens": 870672}
138
- {"current_steps": 138, "total_steps": 190, "loss": 0.0008, "learning_rate": 9.608463116858544e-07, "epoch": 3.5612903225806454, "percentage": 72.63, "elapsed_time": "0:30:17", "remaining_time": "0:11:24", "throughput": "482.42", "total_tokens": 876944}
139
- {"current_steps": 139, "total_steps": 190, "loss": 0.0051, "learning_rate": 9.266990223754069e-07, "epoch": 3.587096774193548, "percentage": 73.16, "elapsed_time": "0:30:30", "remaining_time": "0:11:11", "throughput": "482.52", "total_tokens": 883488}
140
- {"current_steps": 140, "total_steps": 190, "loss": 0.0026, "learning_rate": 8.930309757836517e-07, "epoch": 3.6129032258064515, "percentage": 73.68, "elapsed_time": "0:30:44", "remaining_time": "0:10:58", "throughput": "482.52", "total_tokens": 889824}
141
- {"current_steps": 141, "total_steps": 190, "loss": 0.0041, "learning_rate": 8.598524275237321e-07, "epoch": 3.638709677419355, "percentage": 74.21, "elapsed_time": "0:30:57", "remaining_time": "0:10:45", "throughput": "482.51", "total_tokens": 896176}
142
- {"current_steps": 142, "total_steps": 190, "loss": 0.023, "learning_rate": 8.271734841028553e-07, "epoch": 3.664516129032258, "percentage": 74.74, "elapsed_time": "0:31:10", "remaining_time": "0:10:32", "throughput": "482.38", "total_tokens": 902272}
143
- {"current_steps": 143, "total_steps": 190, "loss": 0.0106, "learning_rate": 7.950040998437541e-07, "epoch": 3.6903225806451614, "percentage": 75.26, "elapsed_time": "0:31:23", "remaining_time": "0:10:19", "throughput": "482.32", "total_tokens": 908512}
144
- {"current_steps": 144, "total_steps": 190, "loss": 0.0238, "learning_rate": 7.633540738525066e-07, "epoch": 3.7161290322580647, "percentage": 75.79, "elapsed_time": "0:31:36", "remaining_time": "0:10:05", "throughput": "482.48", "total_tokens": 915152}
145
- {"current_steps": 145, "total_steps": 190, "loss": 0.0088, "learning_rate": 7.322330470336314e-07, "epoch": 3.741935483870968, "percentage": 76.32, "elapsed_time": "0:31:49", "remaining_time": "0:09:52", "throughput": "482.51", "total_tokens": 921552}
146
- {"current_steps": 146, "total_steps": 190, "loss": 0.0391, "learning_rate": 7.016504991533727e-07, "epoch": 3.767741935483871, "percentage": 76.84, "elapsed_time": "0:32:03", "remaining_time": "0:09:39", "throughput": "482.58", "total_tokens": 928048}
147
- {"current_steps": 147, "total_steps": 190, "loss": 0.0008, "learning_rate": 6.716157459520739e-07, "epoch": 3.793548387096774, "percentage": 77.37, "elapsed_time": "0:32:16", "remaining_time": "0:09:26", "throughput": "482.64", "total_tokens": 934512}
148
- {"current_steps": 148, "total_steps": 190, "loss": 0.0177, "learning_rate": 6.421379363065142e-07, "epoch": 3.8193548387096774, "percentage": 77.89, "elapsed_time": "0:32:29", "remaining_time": "0:09:13", "throughput": "482.62", "total_tokens": 940816}
149
- {"current_steps": 149, "total_steps": 190, "loss": 0.0001, "learning_rate": 6.1322604944307e-07, "epoch": 3.8451612903225807, "percentage": 78.42, "elapsed_time": "0:32:42", "remaining_time": "0:09:00", "throughput": "482.53", "total_tokens": 946992}
150
- {"current_steps": 150, "total_steps": 190, "loss": 0.0002, "learning_rate": 5.848888922025553e-07, "epoch": 3.870967741935484, "percentage": 78.95, "elapsed_time": "0:32:55", "remaining_time": "0:08:46", "throughput": "482.57", "total_tokens": 953424}
151
- {"current_steps": 151, "total_steps": 190, "loss": 0.0044, "learning_rate": 5.571350963575728e-07, "epoch": 3.896774193548387, "percentage": 79.47, "elapsed_time": "0:33:08", "remaining_time": "0:08:33", "throughput": "482.50", "total_tokens": 959616}
152
- {"current_steps": 152, "total_steps": 190, "loss": 0.0015, "learning_rate": 5.299731159831953e-07, "epoch": 3.9225806451612906, "percentage": 80.0, "elapsed_time": "0:33:22", "remaining_time": "0:08:20", "throughput": "482.56", "total_tokens": 966096}
153
- {"current_steps": 153, "total_steps": 190, "loss": 0.0003, "learning_rate": 5.034112248817685e-07, "epoch": 3.9483870967741934, "percentage": 80.53, "elapsed_time": "0:33:35", "remaining_time": "0:08:07", "throughput": "482.53", "total_tokens": 972368}
154
- {"current_steps": 154, "total_steps": 190, "loss": 0.0361, "learning_rate": 4.774575140626317e-07, "epoch": 3.9741935483870967, "percentage": 81.05, "elapsed_time": "0:33:48", "remaining_time": "0:07:54", "throughput": "482.59", "total_tokens": 978848}
155
- {"current_steps": 155, "total_steps": 190, "loss": 0.0005, "learning_rate": 4.5211988927752026e-07, "epoch": 4.0, "percentage": 81.58, "elapsed_time": "0:34:01", "remaining_time": "0:07:40", "throughput": "482.75", "total_tokens": 985520}
156
- {"current_steps": 156, "total_steps": 190, "loss": 0.0022, "learning_rate": 4.27406068612396e-07, "epoch": 4.025806451612903, "percentage": 82.11, "elapsed_time": "0:34:14", "remaining_time": "0:07:27", "throughput": "482.76", "total_tokens": 991904}
157
- {"current_steps": 157, "total_steps": 190, "loss": 0.0212, "learning_rate": 4.033235801364402e-07, "epoch": 4.051612903225807, "percentage": 82.63, "elapsed_time": "0:34:27", "remaining_time": "0:07:14", "throughput": "482.78", "total_tokens": 998288}
158
- {"current_steps": 158, "total_steps": 190, "loss": 0.0003, "learning_rate": 3.798797596089351e-07, "epoch": 4.077419354838709, "percentage": 83.16, "elapsed_time": "0:34:40", "remaining_time": "0:07:01", "throughput": "482.68", "total_tokens": 1004432}
159
- {"current_steps": 159, "total_steps": 190, "loss": 0.0047, "learning_rate": 3.5708174824471947e-07, "epoch": 4.103225806451613, "percentage": 83.68, "elapsed_time": "0:34:54", "remaining_time": "0:06:48", "throughput": "482.59", "total_tokens": 1010608}
160
- {"current_steps": 160, "total_steps": 190, "loss": 0.0014, "learning_rate": 3.3493649053890325e-07, "epoch": 4.129032258064516, "percentage": 84.21, "elapsed_time": "0:35:07", "remaining_time": "0:06:35", "throughput": "482.54", "total_tokens": 1016848}
161
- {"current_steps": 161, "total_steps": 190, "loss": 0.0006, "learning_rate": 3.134507321515107e-07, "epoch": 4.15483870967742, "percentage": 84.74, "elapsed_time": "0:35:20", "remaining_time": "0:06:21", "throughput": "482.62", "total_tokens": 1023360}
162
- {"current_steps": 162, "total_steps": 190, "loss": 0.0003, "learning_rate": 2.9263101785268253e-07, "epoch": 4.180645161290323, "percentage": 85.26, "elapsed_time": "0:35:33", "remaining_time": "0:06:08", "throughput": "482.66", "total_tokens": 1029808}
163
- {"current_steps": 163, "total_steps": 190, "loss": 0.0021, "learning_rate": 2.7248368952908055e-07, "epoch": 4.2064516129032254, "percentage": 85.79, "elapsed_time": "0:35:46", "remaining_time": "0:05:55", "throughput": "482.63", "total_tokens": 1036080}
164
- {"current_steps": 164, "total_steps": 190, "loss": 0.0001, "learning_rate": 2.53014884252083e-07, "epoch": 4.232258064516129, "percentage": 86.32, "elapsed_time": "0:35:59", "remaining_time": "0:05:42", "throughput": "482.54", "total_tokens": 1042240}
165
- {"current_steps": 165, "total_steps": 190, "loss": 0.0007, "learning_rate": 2.3423053240837518e-07, "epoch": 4.258064516129032, "percentage": 86.84, "elapsed_time": "0:36:13", "remaining_time": "0:05:29", "throughput": "482.58", "total_tokens": 1048672}
166
- {"current_steps": 166, "total_steps": 190, "loss": 0.0013, "learning_rate": 2.1613635589349756e-07, "epoch": 4.283870967741936, "percentage": 87.37, "elapsed_time": "0:36:26", "remaining_time": "0:05:16", "throughput": "482.49", "total_tokens": 1054832}
167
- {"current_steps": 167, "total_steps": 190, "loss": 0.0002, "learning_rate": 1.9873786636889908e-07, "epoch": 4.309677419354839, "percentage": 87.89, "elapsed_time": "0:36:39", "remaining_time": "0:05:02", "throughput": "482.55", "total_tokens": 1061312}
168
- {"current_steps": 168, "total_steps": 190, "loss": 0.0011, "learning_rate": 1.8204036358303173e-07, "epoch": 4.335483870967742, "percentage": 88.42, "elapsed_time": "0:36:52", "remaining_time": "0:04:49", "throughput": "482.47", "total_tokens": 1067488}
169
- {"current_steps": 169, "total_steps": 190, "loss": 0.0001, "learning_rate": 1.6604893375699594e-07, "epoch": 4.361290322580645, "percentage": 88.95, "elapsed_time": "0:37:05", "remaining_time": "0:04:36", "throughput": "482.39", "total_tokens": 1073648}
170
- {"current_steps": 170, "total_steps": 190, "loss": 0.0006, "learning_rate": 1.507684480352292e-07, "epoch": 4.387096774193548, "percentage": 89.47, "elapsed_time": "0:37:18", "remaining_time": "0:04:23", "throughput": "482.46", "total_tokens": 1080160}
171
- {"current_steps": 171, "total_steps": 190, "loss": 0.0003, "learning_rate": 1.362035610017079e-07, "epoch": 4.412903225806452, "percentage": 90.0, "elapsed_time": "0:37:32", "remaining_time": "0:04:10", "throughput": "482.60", "total_tokens": 1086832}
172
- {"current_steps": 172, "total_steps": 190, "loss": 0.0002, "learning_rate": 1.223587092621162e-07, "epoch": 4.438709677419355, "percentage": 90.53, "elapsed_time": "0:37:45", "remaining_time": "0:03:57", "throughput": "482.60", "total_tokens": 1093184}
173
- {"current_steps": 173, "total_steps": 190, "loss": 0.0027, "learning_rate": 1.0923811009241142e-07, "epoch": 4.464516129032258, "percentage": 91.05, "elapsed_time": "0:37:58", "remaining_time": "0:03:43", "throughput": "482.69", "total_tokens": 1099728}
174
- {"current_steps": 174, "total_steps": 190, "loss": 0.0002, "learning_rate": 9.684576015420277e-08, "epoch": 4.490322580645161, "percentage": 91.58, "elapsed_time": "0:38:11", "remaining_time": "0:03:30", "throughput": "482.67", "total_tokens": 1106032}
175
- {"current_steps": 175, "total_steps": 190, "loss": 0.0001, "learning_rate": 8.518543427732951e-08, "epoch": 4.516129032258064, "percentage": 92.11, "elapsed_time": "0:38:24", "remaining_time": "0:03:17", "throughput": "482.72", "total_tokens": 1112496}
176
- {"current_steps": 176, "total_steps": 190, "loss": 0.0109, "learning_rate": 7.426068431000883e-08, "epoch": 4.541935483870968, "percentage": 92.63, "elapsed_time": "0:38:37", "remaining_time": "0:03:04", "throughput": "482.85", "total_tokens": 1119152}
177
- {"current_steps": 177, "total_steps": 190, "loss": 0.0039, "learning_rate": 6.407483803691216e-08, "epoch": 4.567741935483871, "percentage": 93.16, "elapsed_time": "0:38:50", "remaining_time": "0:02:51", "throughput": "482.78", "total_tokens": 1125360}
178
- {"current_steps": 178, "total_steps": 190, "loss": 0.0026, "learning_rate": 5.463099816548578e-08, "epoch": 4.593548387096774, "percentage": 93.68, "elapsed_time": "0:39:04", "remaining_time": "0:02:38", "throughput": "482.83", "total_tokens": 1131824}
179
- {"current_steps": 179, "total_steps": 190, "loss": 0.0002, "learning_rate": 4.593204138084006e-08, "epoch": 4.619354838709677, "percentage": 94.21, "elapsed_time": "0:39:17", "remaining_time": "0:02:24", "throughput": "482.85", "total_tokens": 1138224}
180
- {"current_steps": 180, "total_steps": 190, "loss": 0.0044, "learning_rate": 3.798061746947995e-08, "epoch": 4.645161290322581, "percentage": 94.74, "elapsed_time": "0:39:30", "remaining_time": "0:02:11", "throughput": "482.83", "total_tokens": 1144528}
181
- {"current_steps": 181, "total_steps": 190, "loss": 0.0001, "learning_rate": 3.077914851215585e-08, "epoch": 4.670967741935484, "percentage": 95.26, "elapsed_time": "0:39:43", "remaining_time": "0:01:58", "throughput": "482.83", "total_tokens": 1150880}
182
- {"current_steps": 182, "total_steps": 190, "loss": 0.0103, "learning_rate": 2.4329828146074096e-08, "epoch": 4.6967741935483875, "percentage": 95.79, "elapsed_time": "0:39:56", "remaining_time": "0:01:45", "throughput": "482.82", "total_tokens": 1157184}
183
- {"current_steps": 183, "total_steps": 190, "loss": 0.0002, "learning_rate": 1.8634620896695044e-08, "epoch": 4.72258064516129, "percentage": 96.32, "elapsed_time": "0:40:09", "remaining_time": "0:01:32", "throughput": "482.82", "total_tokens": 1163536}
184
- {"current_steps": 184, "total_steps": 190, "loss": 0.0038, "learning_rate": 1.3695261579316776e-08, "epoch": 4.748387096774193, "percentage": 96.84, "elapsed_time": "0:40:23", "remaining_time": "0:01:19", "throughput": "482.82", "total_tokens": 1169888}
185
- {"current_steps": 185, "total_steps": 190, "loss": 0.0039, "learning_rate": 9.513254770636138e-09, "epoch": 4.774193548387097, "percentage": 97.37, "elapsed_time": "0:40:36", "remaining_time": "0:01:05", "throughput": "482.88", "total_tokens": 1176400}
186
- {"current_steps": 186, "total_steps": 190, "loss": 0.0005, "learning_rate": 6.089874350439507e-09, "epoch": 4.8, "percentage": 97.89, "elapsed_time": "0:40:49", "remaining_time": "0:00:52", "throughput": "482.83", "total_tokens": 1182608}
187
- {"current_steps": 187, "total_steps": 190, "loss": 0.0002, "learning_rate": 3.4261631135654174e-09, "epoch": 4.825806451612904, "percentage": 98.42, "elapsed_time": "0:41:02", "remaining_time": "0:00:39", "throughput": "482.85", "total_tokens": 1189008}
188
- {"current_steps": 188, "total_steps": 190, "loss": 0.0011, "learning_rate": 1.5229324522605949e-09, "epoch": 4.851612903225806, "percentage": 98.95, "elapsed_time": "0:41:15", "remaining_time": "0:00:26", "throughput": "482.82", "total_tokens": 1195280}
189
- {"current_steps": 189, "total_steps": 190, "loss": 0.0007, "learning_rate": 3.8076210902182607e-10, "epoch": 4.877419354838709, "percentage": 99.47, "elapsed_time": "0:41:28", "remaining_time": "0:00:13", "throughput": "482.75", "total_tokens": 1201456}
190
- {"current_steps": 190, "total_steps": 190, "loss": 0.0002, "learning_rate": 0.0, "epoch": 4.903225806451613, "percentage": 100.0, "elapsed_time": "0:41:41", "remaining_time": "0:00:00", "throughput": "482.73", "total_tokens": 1207760}
191
- {"current_steps": 190, "total_steps": 190, "epoch": 4.903225806451613, "percentage": 100.0, "elapsed_time": "0:42:42", "remaining_time": "0:00:00", "throughput": "471.27", "total_tokens": 1207760}
 
1
+ {"current_steps": 5, "total_steps": 79, "percentage": 6.33, "elapsed_time": "0:00:00", "remaining_time": "0:00:04"}
2
+ {"current_steps": 10, "total_steps": 79, "percentage": 12.66, "elapsed_time": "0:00:00", "remaining_time": "0:00:05"}
3
+ {"current_steps": 15, "total_steps": 79, "percentage": 18.99, "elapsed_time": "0:00:01", "remaining_time": "0:00:04"}
4
+ {"current_steps": 20, "total_steps": 79, "percentage": 25.32, "elapsed_time": "0:00:01", "remaining_time": "0:00:04"}
5
+ {"current_steps": 25, "total_steps": 79, "percentage": 31.65, "elapsed_time": "0:00:01", "remaining_time": "0:00:04"}
6
+ {"current_steps": 30, "total_steps": 79, "percentage": 37.97, "elapsed_time": "0:00:02", "remaining_time": "0:00:03"}
7
+ {"current_steps": 35, "total_steps": 79, "percentage": 44.3, "elapsed_time": "0:00:02", "remaining_time": "0:00:03"}
8
+ {"current_steps": 40, "total_steps": 79, "percentage": 50.63, "elapsed_time": "0:00:03", "remaining_time": "0:00:03"}
9
+ {"current_steps": 45, "total_steps": 79, "percentage": 56.96, "elapsed_time": "0:00:03", "remaining_time": "0:00:02"}
10
+ {"current_steps": 50, "total_steps": 79, "percentage": 63.29, "elapsed_time": "0:00:03", "remaining_time": "0:00:02"}
11
+ {"current_steps": 55, "total_steps": 79, "percentage": 69.62, "elapsed_time": "0:00:04", "remaining_time": "0:00:01"}
12
+ {"current_steps": 60, "total_steps": 79, "percentage": 75.95, "elapsed_time": "0:00:04", "remaining_time": "0:00:01"}
13
+ {"current_steps": 65, "total_steps": 79, "percentage": 82.28, "elapsed_time": "0:00:05", "remaining_time": "0:00:01"}
14
+ {"current_steps": 70, "total_steps": 79, "percentage": 88.61, "elapsed_time": "0:00:05", "remaining_time": "0:00:00"}
15
+ {"current_steps": 75, "total_steps": 79, "percentage": 94.94, "elapsed_time": "0:00:05", "remaining_time": "0:00:00"}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
training_args.yaml CHANGED
@@ -1,29 +1,18 @@
1
- bf16: true
2
  cutoff_len: 1024
3
- dataset: truth_train_0716_2
4
  dataset_dir: data
5
- ddp_timeout: 180000000
6
- deepspeed: cache/ds_z2_config.json
7
- do_train: true
8
  finetuning_type: full
9
  flash_attn: auto
10
- gradient_accumulation_steps: 8
11
- include_num_input_tokens_seen: true
12
- learning_rate: 5.0e-06
13
- logging_steps: 1
14
- lr_scheduler_type: cosine
15
- max_grad_norm: 1.0
16
  max_samples: 100000
17
- model_name_or_path: meta-llama/Meta-Llama-3.1-8B-Instruct
18
- num_train_epochs: 5.0
19
- optim: adamw_torch
20
- output_dir: saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2
21
- packing: false
22
- per_device_train_batch_size: 2
23
- plot_loss: true
24
  preprocessing_num_workers: 16
25
- report_to: none
26
- save_steps: 5000
27
  stage: sft
 
28
  template: llama3
29
- warmup_steps: 10
 
 
1
  cutoff_len: 1024
 
2
  dataset_dir: data
3
+ do_predict: true
4
+ eval_dataset: truth_dev_0716_2
 
5
  finetuning_type: full
6
  flash_attn: auto
7
+ max_new_tokens: 512
 
 
 
 
 
8
  max_samples: 100000
9
+ model_name_or_path: saves/LLaMA3.1-8B-Chat/full/train_2024-07-30-02-47-53_llama3.1_truthqa_bench2
10
+ output_dir: saves/LLaMA3.1-8B-Chat/full/eval_2024-07-30-02-47-53_llama3.1_truthqa_bench2
11
+ per_device_eval_batch_size: 2
12
+ predict_with_generate: true
 
 
 
13
  preprocessing_num_workers: 16
14
+ quantization_method: bitsandbytes
 
15
  stage: sft
16
+ temperature: 0.95
17
  template: llama3
18
+ top_p: 0.7