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--- |
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library_name: peft |
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license: apache-2.0 |
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base_model: JackFram/llama-160m |
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tags: |
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- axolotl |
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- generated_from_trainer |
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model-index: |
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- name: e0073826-5531-478d-a60d-1a0ce8835544 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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```yaml |
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adapter: lora |
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base_model: JackFram/llama-160m |
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bf16: auto |
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chat_template: llama3 |
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dataset_prepared_path: null |
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datasets: |
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- data_files: |
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- c3a48bca22943176_train_data.json |
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ds_type: json |
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format: custom |
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path: /workspace/input_data/c3a48bca22943176_train_data.json |
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type: |
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field_instruction: keywords |
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field_output: text |
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format: '{instruction}' |
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no_input_format: '{instruction}' |
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system_format: '{system}' |
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system_prompt: '' |
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debug: null |
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deepspeed: null |
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early_stopping_patience: null |
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eval_max_new_tokens: 128 |
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eval_table_size: null |
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evals_per_epoch: 4 |
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flash_attention: true |
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fp16: null |
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fsdp: null |
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fsdp_config: null |
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gradient_accumulation_steps: 4 |
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gradient_checkpointing: true |
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gradient_clipping: 1.0 |
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group_by_length: false |
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hub_model_id: ardaspear/e0073826-5531-478d-a60d-1a0ce8835544 |
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hub_repo: null |
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hub_strategy: checkpoint |
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hub_token: null |
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learning_rate: 5.0e-05 |
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load_in_4bit: false |
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load_in_8bit: false |
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local_rank: 0 |
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logging_steps: 3 |
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lora_alpha: 32 |
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lora_dropout: 0.05 |
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lora_fan_in_fan_out: null |
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lora_model_dir: null |
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lora_r: 16 |
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lora_target_linear: true |
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lr_scheduler: cosine |
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max_steps: 100 |
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micro_batch_size: 8 |
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mlflow_experiment_name: /tmp/c3a48bca22943176_train_data.json |
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model_type: AutoModelForCausalLM |
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num_epochs: 3 |
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optimizer: adamw_bnb_8bit |
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output_dir: miner_id_24 |
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pad_to_sequence_len: true |
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resume_from_checkpoint: null |
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s2_attention: null |
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sample_packing: false |
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saves_per_epoch: 4 |
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sequence_len: 1024 |
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special_tokens: |
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pad_token: </s> |
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strict: false |
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tf32: false |
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tokenizer_type: AutoTokenizer |
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train_on_inputs: false |
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trust_remote_code: true |
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val_set_size: 0.05 |
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wandb_entity: techspear-hub |
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wandb_mode: online |
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wandb_name: b998dead-53af-4583-bf44-4616d08e8afd |
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wandb_project: Gradients-On-Five |
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wandb_run: your_name |
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wandb_runid: b998dead-53af-4583-bf44-4616d08e8afd |
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warmup_steps: 10 |
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weight_decay: 0.01 |
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xformers_attention: null |
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``` |
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</details><br> |
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# e0073826-5531-478d-a60d-1a0ce8835544 |
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This model is a fine-tuned version of [JackFram/llama-160m](https://huggingface.co/JackFram/llama-160m) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.3959 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- training_steps: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| No log | 0.0007 | 1 | 6.3021 | |
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| 6.2928 | 0.0062 | 9 | 6.2544 | |
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| 6.1336 | 0.0124 | 18 | 5.9688 | |
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| 5.8615 | 0.0186 | 27 | 5.6790 | |
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| 5.5222 | 0.0248 | 36 | 5.4078 | |
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| 5.2112 | 0.0310 | 45 | 5.1390 | |
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| 4.8747 | 0.0373 | 54 | 4.8816 | |
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| 4.6527 | 0.0435 | 63 | 4.6716 | |
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| 4.5453 | 0.0497 | 72 | 4.5196 | |
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| 4.4503 | 0.0559 | 81 | 4.4360 | |
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| 4.3793 | 0.0621 | 90 | 4.4022 | |
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| 4.2764 | 0.0683 | 99 | 4.3959 | |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.46.0 |
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- Pytorch 2.5.0+cu124 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.1 |
