df: /root/.triton/autotune: No such file or directory
[INFO|tokenization_utils_base.py:2159] 2025-01-05 11:08:24,607 >> loading file tokenizer.json
[INFO|tokenization_utils_base.py:2159] 2025-01-05 11:08:24,607 >> loading file added_tokens.json
[INFO|tokenization_utils_base.py:2159] 2025-01-05 11:08:24,607 >> loading file special_tokens_map.json
[INFO|tokenization_utils_base.py:2159] 2025-01-05 11:08:24,607 >> loading file tokenizer_config.json
[WARNING|logging.py:313] 2025-01-05 11:08:24,971 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.

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Converting format of dataset: 100%|██████████| 2932/2932 [00:00<00:00, 52561.23 examples/s]

Generating train split: 0 examples [00:00, ? examples/s]
Generating train split: 586 examples [00:00, 75563.75 examples/s]

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Converting format of dataset: 100%|██████████| 586/586 [00:00<00:00, 43964.98 examples/s]

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Running tokenizer on dataset: 100%|██████████| 2932/2932 [00:01<00:00, 1470.20 examples/s]

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Running tokenizer on dataset: 100%|██████████| 586/586 [00:00<00:00, 1598.16 examples/s]
[INFO|configuration_utils.py:731] 2025-01-05 11:08:29,400 >> loading configuration file /home/.atp/models/llama3_cn_8b_instruct/config.json
[INFO|configuration_utils.py:800] 2025-01-05 11:08:29,402 >> Model config LlamaConfig {
"_name_or_path": "/home/.atp/models/llama3_cn_8b_instruct",
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": 128001,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 8192,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 8,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 500000.0,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.42.4",
"use_cache": true,
"vocab_size": 128256
}

[INFO|modeling_utils.py:3553] 2025-01-05 11:08:29,440 >> loading weights file /home/.atp/models/llama3_cn_8b_instruct/model.safetensors.index.json
[INFO|modeling_utils.py:1531] 2025-01-05 11:08:29,444 >> Instantiating LlamaForCausalLM model under default dtype torch.float16.
[INFO|configuration_utils.py:1000] 2025-01-05 11:08:29,447 >> Generate config GenerationConfig {
"bos_token_id": 128000,
"eos_token_id": 128001
}


Loading checkpoint shards:   0%|          | 0/4 [00:00<?, ?it/s]
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Loading checkpoint shards: 100%|██████████| 4/4 [00:10<00:00,  2.61s/it]
[INFO|modeling_utils.py:4364] 2025-01-05 11:08:39,938 >> All model checkpoint weights were used when initializing LlamaForCausalLM.

[INFO|modeling_utils.py:4372] 2025-01-05 11:08:39,938 >> All the weights of LlamaForCausalLM were initialized from the model checkpoint at /home/.atp/models/llama3_cn_8b_instruct.
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.
[INFO|configuration_utils.py:953] 2025-01-05 11:08:39,946 >> loading configuration file /home/.atp/models/llama3_cn_8b_instruct/generation_config.json
[INFO|configuration_utils.py:1000] 2025-01-05 11:08:39,946 >> Generate config GenerationConfig {
"bos_token_id": 128000,
"do_sample": true,
"eos_token_id": 128001,
"max_length": 4096,
"temperature": 0.6,
"top_p": 0.9
}

Detected kernel version 3.10.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.
[INFO|trainer.py:642] 2025-01-05 11:08:41,722 >> Using auto half precision backend
[INFO|trainer.py:2128] 2025-01-05 11:08:42,507 >> ***** Running training *****
[INFO|trainer.py:2129] 2025-01-05 11:08:42,508 >>   Num examples = 2,932
[INFO|trainer.py:2130] 2025-01-05 11:08:42,508 >>   Num Epochs = 5
[INFO|trainer.py:2131] 2025-01-05 11:08:42,508 >>   Instantaneous batch size per device = 4
[INFO|trainer.py:2134] 2025-01-05 11:08:42,508 >>   Total train batch size (w. parallel, distributed & accumulation) = 4
[INFO|trainer.py:2135] 2025-01-05 11:08:42,508 >>   Gradient Accumulation steps = 1
[INFO|trainer.py:2136] 2025-01-05 11:08:42,508 >>   Total optimization steps = 3,665
[INFO|trainer.py:2137] 2025-01-05 11:08:42,512 >>   Number of trainable parameters = 20,971,520

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20%|██        | 733/3665 [08:15<29:49,  1.64it/s][INFO|trainer.py:3478] 2025-01-05 11:16:58,158 >> Saving model checkpoint to /work/train_output/checkpoint-733
[INFO|configuration_utils.py:731] 2025-01-05 11:16:58,199 >> loading configuration file /home/.atp/models/llama3_cn_8b_instruct/config.json
[INFO|configuration_utils.py:800] 2025-01-05 11:16:58,200 >> Model config LlamaConfig {
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": 128001,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 8192,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 8,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 500000.0,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.42.4",
"use_cache": true,
"vocab_size": 128256
}

[INFO|tokenization_utils_base.py:2574] 2025-01-05 11:16:58,734 >> tokenizer config file saved in /work/train_output/checkpoint-733/tokenizer_config.json
[INFO|tokenization_utils_base.py:2583] 2025-01-05 11:16:58,736 >> Special tokens file saved in /work/train_output/checkpoint-733/special_tokens_map.json

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[INFO|configuration_utils.py:731] 2025-01-05 11:25:13,972 >> loading configuration file /home/.atp/models/llama3_cn_8b_instruct/config.json
[INFO|configuration_utils.py:800] 2025-01-05 11:25:13,973 >> Model config LlamaConfig {
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": 128001,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 8192,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 8,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 500000.0,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.42.4",
"use_cache": true,
"vocab_size": 128256
}

[INFO|tokenization_utils_base.py:2574] 2025-01-05 11:25:14,478 >> tokenizer config file saved in /work/train_output/checkpoint-1466/tokenizer_config.json
[INFO|tokenization_utils_base.py:2583] 2025-01-05 11:25:14,481 >> Special tokens file saved in /work/train_output/checkpoint-1466/special_tokens_map.json
[INFO|trainer.py:3570] 2025-01-05 11:25:14,683 >> Deleting older checkpoint [/work/train_output/checkpoint-733] due to args.save_total_limit

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[INFO|configuration_utils.py:731] 2025-01-05 11:33:31,469 >> loading configuration file /home/.atp/models/llama3_cn_8b_instruct/config.json
[INFO|configuration_utils.py:800] 2025-01-05 11:33:31,470 >> Model config LlamaConfig {
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": 128001,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 8192,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 8,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 500000.0,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.42.4",
"use_cache": true,
"vocab_size": 128256
}

[INFO|tokenization_utils_base.py:2574] 2025-01-05 11:33:31,980 >> tokenizer config file saved in /work/train_output/checkpoint-2199/tokenizer_config.json
[INFO|tokenization_utils_base.py:2583] 2025-01-05 11:33:31,982 >> Special tokens file saved in /work/train_output/checkpoint-2199/special_tokens_map.json
[INFO|trainer.py:3570] 2025-01-05 11:33:32,148 >> Deleting older checkpoint [/work/train_output/checkpoint-1466] due to args.save_total_limit

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[INFO|configuration_utils.py:731] 2025-01-05 11:41:47,575 >> loading configuration file /home/.atp/models/llama3_cn_8b_instruct/config.json
[INFO|configuration_utils.py:800] 2025-01-05 11:41:47,576 >> Model config LlamaConfig {
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": 128001,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 8192,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 8,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 500000.0,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.42.4",
"use_cache": true,
"vocab_size": 128256
}

[INFO|tokenization_utils_base.py:2574] 2025-01-05 11:41:48,080 >> tokenizer config file saved in /work/train_output/checkpoint-2932/tokenizer_config.json
[INFO|tokenization_utils_base.py:2583] 2025-01-05 11:41:48,083 >> Special tokens file saved in /work/train_output/checkpoint-2932/special_tokens_map.json
[INFO|trainer.py:3570] 2025-01-05 11:41:48,249 >> Deleting older checkpoint [/work/train_output/checkpoint-2199] due to args.save_total_limit

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[INFO|configuration_utils.py:731] 2025-01-05 11:50:03,936 >> loading configuration file /home/.atp/models/llama3_cn_8b_instruct/config.json
[INFO|configuration_utils.py:800] 2025-01-05 11:50:03,937 >> Model config LlamaConfig {
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": 128001,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 8192,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 8,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 500000.0,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.42.4",
"use_cache": true,
"vocab_size": 128256
}

[INFO|tokenization_utils_base.py:2574] 2025-01-05 11:50:04,453 >> tokenizer config file saved in /work/train_output/checkpoint-3665/tokenizer_config.json
[INFO|tokenization_utils_base.py:2583] 2025-01-05 11:50:04,455 >> Special tokens file saved in /work/train_output/checkpoint-3665/special_tokens_map.json
[INFO|trainer.py:3570] 2025-01-05 11:50:04,619 >> Deleting older checkpoint [/work/train_output/checkpoint-2932] due to args.save_total_limit
[INFO|trainer.py:3478] 2025-01-05 11:50:04,656 >> Saving model checkpoint to /work/train_output/checkpoint-3665
[INFO|configuration_utils.py:731] 2025-01-05 11:50:04,684 >> loading configuration file /home/.atp/models/llama3_cn_8b_instruct/config.json
[INFO|configuration_utils.py:800] 2025-01-05 11:50:04,684 >> Model config LlamaConfig {
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": 128001,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 8192,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 8,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 500000.0,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.42.4",
"use_cache": true,
"vocab_size": 128256
}

[INFO|tokenization_utils_base.py:2574] 2025-01-05 11:50:05,163 >> tokenizer config file saved in /work/train_output/checkpoint-3665/tokenizer_config.json
[INFO|tokenization_utils_base.py:2583] 2025-01-05 11:50:05,165 >> Special tokens file saved in /work/train_output/checkpoint-3665/special_tokens_map.json
[INFO|trainer.py:2383] 2025-01-05 11:50:05,336 >>

Training completed. Do not forget to share your model on huggingface.co/models =)





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[INFO|trainer.py:3478] 2025-01-05 11:50:05,357 >> Saving model checkpoint to /work/train_output/
[INFO|configuration_utils.py:731] 2025-01-05 11:50:05,388 >> loading configuration file /home/.atp/models/llama3_cn_8b_instruct/config.json
[INFO|configuration_utils.py:800] 2025-01-05 11:50:05,389 >> Model config LlamaConfig {
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": 128001,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 8192,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 8,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 500000.0,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.42.4",
"use_cache": true,
"vocab_size": 128256
}

[INFO|tokenization_utils_base.py:2574] 2025-01-05 11:50:05,829 >> tokenizer config file saved in /work/train_output/tokenizer_config.json
[INFO|tokenization_utils_base.py:2583] 2025-01-05 11:50:05,831 >> Special tokens file saved in /work/train_output/special_tokens_map.json
[INFO|trainer.py:3788] 2025-01-05 11:50:06,181 >>
***** Running Prediction *****
[INFO|trainer.py:3790] 2025-01-05 11:50:06,181 >>   Num examples = 586
[INFO|trainer.py:3793] 2025-01-05 11:50:06,181 >>   Batch size = 4

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100%|██████████| 147/147 [12:05<00:00,  3.37s/it]Building prefix dict from the default dictionary ...
Dumping model to file cache /tmp/jieba.cache
Loading model cost 0.589 seconds.
Prefix dict has been built successfully.

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[INFO|modelcard.py:449] 2025-01-05 12:02:16,690 >> Dropping the following result as it does not have all the necessary fields:
{'task': {'name': 'Causal Language Modeling', 'type': 'text-generation'}}
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using `tokenizers` before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using `tokenizers` before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using `tokenizers` before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using `tokenizers` before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)