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[INFO|2024-11-25 07:48:02] parser.py:355 >> Process rank: 0, device: cuda:0, n_gpu: 1, distributed training: True, compute dtype: torch.bfloat16
[INFO|2024-11-25 07:48:02] parser.py:355 >> Process rank: 3, device: cuda:3, n_gpu: 1, distributed training: True, compute dtype: torch.bfloat16
[INFO|2024-11-25 07:48:02] parser.py:355 >> Process rank: 2, device: cuda:2, n_gpu: 1, distributed training: True, compute dtype: torch.bfloat16
[INFO|2024-11-25 07:48:02] parser.py:355 >> Process rank: 1, device: cuda:1, n_gpu: 1, distributed training: True, compute dtype: torch.bfloat16
[INFO|2024-11-25 07:48:02] configuration_utils.py:679 >> loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a/config.json
[INFO|2024-11-25 07:48:02] configuration_utils.py:746 >> Model config LlamaConfig {
"_name_or_path": "meta-llama/Meta-Llama-3-8B-Instruct",
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": 128009,
"head_dim": 128,
"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": "4.46.1",
"use_cache": true,
"vocab_size": 128256
}
[INFO|2024-11-25 07:48:03] tokenization_utils_base.py:2211 >> loading file tokenizer.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a/tokenizer.json
[INFO|2024-11-25 07:48:03] tokenization_utils_base.py:2211 >> loading file tokenizer.model from cache at None
[INFO|2024-11-25 07:48:03] tokenization_utils_base.py:2211 >> loading file added_tokens.json from cache at None
[INFO|2024-11-25 07:48:03] tokenization_utils_base.py:2211 >> loading file special_tokens_map.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a/special_tokens_map.json
[INFO|2024-11-25 07:48:03] tokenization_utils_base.py:2211 >> loading file tokenizer_config.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a/tokenizer_config.json
[INFO|2024-11-25 07:48:03] tokenization_utils_base.py:2475 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
[INFO|2024-11-25 07:48:04] configuration_utils.py:679 >> loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a/config.json
[INFO|2024-11-25 07:48:04] configuration_utils.py:746 >> Model config LlamaConfig {
"_name_or_path": "meta-llama/Meta-Llama-3-8B-Instruct",
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": 128009,
"head_dim": 128,
"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": "4.46.1",
"use_cache": true,
"vocab_size": 128256
}
[INFO|2024-11-25 07:48:05] tokenization_utils_base.py:2211 >> loading file tokenizer.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a/tokenizer.json
[INFO|2024-11-25 07:48:05] tokenization_utils_base.py:2211 >> loading file tokenizer.model from cache at None
[INFO|2024-11-25 07:48:05] tokenization_utils_base.py:2211 >> loading file added_tokens.json from cache at None
[INFO|2024-11-25 07:48:05] tokenization_utils_base.py:2211 >> loading file special_tokens_map.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a/special_tokens_map.json
[INFO|2024-11-25 07:48:05] tokenization_utils_base.py:2211 >> loading file tokenizer_config.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a/tokenizer_config.json
[INFO|2024-11-25 07:48:05] tokenization_utils_base.py:2475 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
[INFO|2024-11-25 07:48:05] logging.py:157 >> Replace eos token: <|eot_id|>
[INFO|2024-11-25 07:48:05] logging.py:157 >> Add pad token: <|eot_id|>
[INFO|2024-11-25 07:48:05] logging.py:157 >> Loading dataset ragtruth_base_data/train_hallucination_detection_1125.json...
[INFO|2024-11-25 07:48:15] configuration_utils.py:679 >> loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a/config.json
[INFO|2024-11-25 07:48:15] configuration_utils.py:746 >> Model config LlamaConfig {
"_name_or_path": "meta-llama/Meta-Llama-3-8B-Instruct",
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": 128009,
"head_dim": 128,
"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": "4.46.1",
"use_cache": true,
"vocab_size": 128256
}
[INFO|2024-11-25 07:48:15] modeling_utils.py:3937 >> loading weights file model.safetensors from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a/model.safetensors.index.json
[INFO|2024-11-25 07:48:15] modeling_utils.py:1670 >> Instantiating LlamaForCausalLM model under default dtype torch.bfloat16.
[INFO|2024-11-25 07:48:15] configuration_utils.py:1096 >> Generate config GenerationConfig {
"bos_token_id": 128000,
"eos_token_id": 128009
}
[INFO|2024-11-25 07:48:19] modeling_utils.py:4800 >> All model checkpoint weights were used when initializing LlamaForCausalLM.
[INFO|2024-11-25 07:48:19] modeling_utils.py:4808 >> All the weights of LlamaForCausalLM were initialized from the model checkpoint at meta-llama/Meta-Llama-3-8B-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|2024-11-25 07:48:19] configuration_utils.py:1051 >> loading configuration file generation_config.json from cache at /root/.cache/huggingface/hub/models--meta-llama--Meta-Llama-3-8B-Instruct/snapshots/5f0b02c75b57c5855da9ae460ce51323ea669d8a/generation_config.json
[INFO|2024-11-25 07:48:19] configuration_utils.py:1096 >> Generate config GenerationConfig {
"bos_token_id": 128000,
"do_sample": true,
"eos_token_id": [
128001,
128009
],
"max_length": 4096,
"temperature": 0.6,
"top_p": 0.9
}
[INFO|2024-11-25 07:48:19] logging.py:157 >> Gradient checkpointing enabled.
[INFO|2024-11-25 07:48:19] logging.py:157 >> Using torch SDPA for faster training and inference.
[INFO|2024-11-25 07:48:19] logging.py:157 >> Upcasting trainable params to float32.
[INFO|2024-11-25 07:48:19] logging.py:157 >> Fine-tuning method: Full
[INFO|2024-11-25 07:48:19] logging.py:157 >> trainable params: 8,030,261,248 || all params: 8,030,261,248 || trainable%: 100.0000
[INFO|2024-11-25 07:48:19] trainer.py:698 >> Using auto half precision backend
[INFO|2024-11-25 07:48:19] deepspeed.py:334 >> Detected ZeRO Offload and non-DeepSpeed optimizers: This combination should work as long as the custom optimizer has both CPU and GPU implementation (except LAMB)
[INFO|2024-11-25 07:49:10] trainer.py:2313 >> ***** Running training *****
[INFO|2024-11-25 07:49:10] trainer.py:2314 >> Num examples = 15,090
[INFO|2024-11-25 07:49:10] trainer.py:2315 >> Num Epochs = 3
[INFO|2024-11-25 07:49:10] trainer.py:2316 >> Instantaneous batch size per device = 1
[INFO|2024-11-25 07:49:10] trainer.py:2319 >> Total train batch size (w. parallel, distributed & accumulation) = 32
[INFO|2024-11-25 07:49:10] trainer.py:2320 >> Gradient Accumulation steps = 8
[INFO|2024-11-25 07:49:10] trainer.py:2321 >> Total optimization steps = 1,413
[INFO|2024-11-25 07:49:10] trainer.py:2322 >> Number of trainable parameters = 8,030,261,248
[INFO|2024-11-25 07:49:39] logging.py:157 >> {'loss': 1.2577, 'learning_rate': 5.0000e-07, 'epoch': 0.00}
[INFO|2024-11-25 07:50:00] logging.py:157 >> {'loss': 1.1764, 'learning_rate': 1.0000e-06, 'epoch': 0.00}
[INFO|2024-11-25 07:50:21] logging.py:157 >> {'loss': 1.1581, 'learning_rate': 1.5000e-06, 'epoch': 0.01}
[INFO|2024-11-25 07:50:42] logging.py:157 >> {'loss': 0.9151, 'learning_rate': 2.0000e-06, 'epoch': 0.01}
[INFO|2024-11-25 07:51:03] logging.py:157 >> {'loss': 0.5946, 'learning_rate': 2.5000e-06, 'epoch': 0.01}
[INFO|2024-11-25 07:51:23] logging.py:157 >> {'loss': 0.5140, 'learning_rate': 3.0000e-06, 'epoch': 0.01}
[INFO|2024-11-25 07:51:46] logging.py:157 >> {'loss': 0.3226, 'learning_rate': 3.5000e-06, 'epoch': 0.01}
[INFO|2024-11-25 07:52:07] logging.py:157 >> {'loss': 0.3853, 'learning_rate': 4.0000e-06, 'epoch': 0.02}
[INFO|2024-11-25 07:52:28] logging.py:157 >> {'loss': 0.2983, 'learning_rate': 4.5000e-06, 'epoch': 0.02}
[INFO|2024-11-25 07:52:49] logging.py:157 >> {'loss': 0.4318, 'learning_rate': 5.0000e-06, 'epoch': 0.02}
[INFO|2024-11-25 07:53:10] logging.py:157 >> {'loss': 0.4925, 'learning_rate': 5.0000e-06, 'epoch': 0.02}
[INFO|2024-11-25 07:53:31] logging.py:157 >> {'loss': 0.4128, 'learning_rate': 5.0000e-06, 'epoch': 0.03}
[INFO|2024-11-25 07:53:52] logging.py:157 >> {'loss': 0.3941, 'learning_rate': 4.9999e-06, 'epoch': 0.03}
[INFO|2024-11-25 07:54:13] logging.py:157 >> {'loss': 0.5270, 'learning_rate': 4.9999e-06, 'epoch': 0.03}
[INFO|2024-11-25 07:54:35] logging.py:157 >> {'loss': 0.5217, 'learning_rate': 4.9998e-06, 'epoch': 0.03}
[INFO|2024-11-25 07:54:56] logging.py:157 >> {'loss': 0.2620, 'learning_rate': 4.9998e-06, 'epoch': 0.03}
[INFO|2024-11-25 07:55:18] logging.py:157 >> {'loss': 0.5101, 'learning_rate': 4.9997e-06, 'epoch': 0.04}
[INFO|2024-11-25 07:55:39] logging.py:157 >> {'loss': 0.3760, 'learning_rate': 4.9996e-06, 'epoch': 0.04}
[INFO|2024-11-25 07:56:00] logging.py:157 >> {'loss': 0.3747, 'learning_rate': 4.9995e-06, 'epoch': 0.04}
[INFO|2024-11-25 07:56:20] logging.py:157 >> {'loss': 0.3933, 'learning_rate': 4.9994e-06, 'epoch': 0.04}
[INFO|2024-11-25 07:56:44] logging.py:157 >> {'loss': 0.3696, 'learning_rate': 4.9992e-06, 'epoch': 0.04}
[INFO|2024-11-25 07:57:06] logging.py:157 >> {'loss': 0.3125, 'learning_rate': 4.9991e-06, 'epoch': 0.05}
[INFO|2024-11-25 07:57:26] logging.py:157 >> {'loss': 0.4218, 'learning_rate': 4.9989e-06, 'epoch': 0.05}
[INFO|2024-11-25 07:57:48] logging.py:157 >> {'loss': 0.3827, 'learning_rate': 4.9988e-06, 'epoch': 0.05}
[INFO|2024-11-25 07:58:08] logging.py:157 >> {'loss': 0.4637, 'learning_rate': 4.9986e-06, 'epoch': 0.05}
[INFO|2024-11-25 07:58:29] logging.py:157 >> {'loss': 0.3562, 'learning_rate': 4.9984e-06, 'epoch': 0.06}
[INFO|2024-11-25 07:58:50] logging.py:157 >> {'loss': 0.3842, 'learning_rate': 4.9982e-06, 'epoch': 0.06}
[INFO|2024-11-25 07:59:12] logging.py:157 >> {'loss': 0.3048, 'learning_rate': 4.9980e-06, 'epoch': 0.06}
[INFO|2024-11-25 07:59:34] logging.py:157 >> {'loss': 0.3621, 'learning_rate': 4.9977e-06, 'epoch': 0.06}
[INFO|2024-11-25 07:59:54] logging.py:157 >> {'loss': 0.2974, 'learning_rate': 4.9975e-06, 'epoch': 0.06}
[INFO|2024-11-25 08:00:15] logging.py:157 >> {'loss': 0.4450, 'learning_rate': 4.9972e-06, 'epoch': 0.07}
[INFO|2024-11-25 08:00:37] logging.py:157 >> {'loss': 0.3759, 'learning_rate': 4.9970e-06, 'epoch': 0.07}
[INFO|2024-11-25 08:00:57] logging.py:157 >> {'loss': 0.3232, 'learning_rate': 4.9967e-06, 'epoch': 0.07}
[INFO|2024-11-25 08:01:18] logging.py:157 >> {'loss': 0.4248, 'learning_rate': 4.9964e-06, 'epoch': 0.07}
[INFO|2024-11-25 08:01:39] logging.py:157 >> {'loss': 0.2229, 'learning_rate': 4.9961e-06, 'epoch': 0.07}
[INFO|2024-11-25 08:01:59] logging.py:157 >> {'loss': 0.3160, 'learning_rate': 4.9958e-06, 'epoch': 0.08}
[INFO|2024-11-25 08:02:20] logging.py:157 >> {'loss': 0.3061, 'learning_rate': 4.9954e-06, 'epoch': 0.08}
[INFO|2024-11-25 08:02:41] logging.py:157 >> {'loss': 0.3889, 'learning_rate': 4.9951e-06, 'epoch': 0.08}
[INFO|2024-11-25 08:03:02] logging.py:157 >> {'loss': 0.3944, 'learning_rate': 4.9947e-06, 'epoch': 0.08}
[INFO|2024-11-25 08:03:22] logging.py:157 >> {'loss': 0.5437, 'learning_rate': 4.9944e-06, 'epoch': 0.08}
[INFO|2024-11-25 08:03:43] logging.py:157 >> {'loss': 0.3570, 'learning_rate': 4.9940e-06, 'epoch': 0.09}
[INFO|2024-11-25 08:04:03] logging.py:157 >> {'loss': 0.3081, 'learning_rate': 4.9936e-06, 'epoch': 0.09}
[INFO|2024-11-25 08:04:25] logging.py:157 >> {'loss': 0.3468, 'learning_rate': 4.9932e-06, 'epoch': 0.09}
[INFO|2024-11-25 08:04:46] logging.py:157 >> {'loss': 0.3266, 'learning_rate': 4.9928e-06, 'epoch': 0.09}
[INFO|2024-11-25 08:05:07] logging.py:157 >> {'loss': 0.3799, 'learning_rate': 4.9923e-06, 'epoch': 0.10}
[INFO|2024-11-25 08:05:30] logging.py:157 >> {'loss': 0.3149, 'learning_rate': 4.9919e-06, 'epoch': 0.10}
[INFO|2024-11-25 08:05:51] logging.py:157 >> {'loss': 0.2163, 'learning_rate': 4.9914e-06, 'epoch': 0.10}
[INFO|2024-11-25 08:06:12] logging.py:157 >> {'loss': 0.4008, 'learning_rate': 4.9910e-06, 'epoch': 0.10}
[INFO|2024-11-25 08:06:33] logging.py:157 >> {'loss': 0.3937, 'learning_rate': 4.9905e-06, 'epoch': 0.10}
[INFO|2024-11-25 08:06:54] logging.py:157 >> {'loss': 0.3810, 'learning_rate': 4.9900e-06, 'epoch': 0.11}
[INFO|2024-11-25 08:07:14] logging.py:157 >> {'loss': 0.2995, 'learning_rate': 4.9895e-06, 'epoch': 0.11}
[INFO|2024-11-25 08:07:35] logging.py:157 >> {'loss': 0.2401, 'learning_rate': 4.9890e-06, 'epoch': 0.11}
[INFO|2024-11-25 08:07:56] logging.py:157 >> {'loss': 0.3294, 'learning_rate': 4.9884e-06, 'epoch': 0.11}
[INFO|2024-11-25 08:08:16] logging.py:157 >> {'loss': 0.4972, 'learning_rate': 4.9879e-06, 'epoch': 0.11}
[INFO|2024-11-25 08:08:37] logging.py:157 >> {'loss': 0.4146, 'learning_rate': 4.9873e-06, 'epoch': 0.12}
[INFO|2024-11-25 08:08:58] logging.py:157 >> {'loss': 0.3277, 'learning_rate': 4.9867e-06, 'epoch': 0.12}
[INFO|2024-11-25 08:09:20] logging.py:157 >> {'loss': 0.2963, 'learning_rate': 4.9862e-06, 'epoch': 0.12}
[INFO|2024-11-25 08:09:41] logging.py:157 >> {'loss': 0.2798, 'learning_rate': 4.9856e-06, 'epoch': 0.12}
[INFO|2024-11-25 08:10:02] logging.py:157 >> {'loss': 0.3764, 'learning_rate': 4.9850e-06, 'epoch': 0.13}
[INFO|2024-11-25 08:10:25] logging.py:157 >> {'loss': 0.2544, 'learning_rate': 4.9843e-06, 'epoch': 0.13}
[INFO|2024-11-25 08:10:47] logging.py:157 >> {'loss': 0.3421, 'learning_rate': 4.9837e-06, 'epoch': 0.13}
[INFO|2024-11-25 08:11:08] logging.py:157 >> {'loss': 0.4167, 'learning_rate': 4.9831e-06, 'epoch': 0.13}
[INFO|2024-11-25 08:11:29] logging.py:157 >> {'loss': 0.1973, 'learning_rate': 4.9824e-06, 'epoch': 0.13}
[INFO|2024-11-25 08:11:49] logging.py:157 >> {'loss': 0.3211, 'learning_rate': 4.9817e-06, 'epoch': 0.14}
[INFO|2024-11-25 08:12:10] logging.py:157 >> {'loss': 0.2813, 'learning_rate': 4.9811e-06, 'epoch': 0.14}
[INFO|2024-11-25 08:12:30] logging.py:157 >> {'loss': 0.2489, 'learning_rate': 4.9804e-06, 'epoch': 0.14}
[INFO|2024-11-25 08:12:52] logging.py:157 >> {'loss': 0.3817, 'learning_rate': 4.9797e-06, 'epoch': 0.14}
[INFO|2024-11-25 08:13:12] logging.py:157 >> {'loss': 0.2673, 'learning_rate': 4.9789e-06, 'epoch': 0.14}
[INFO|2024-11-25 08:13:33] logging.py:157 >> {'loss': 0.2844, 'learning_rate': 4.9782e-06, 'epoch': 0.15}
[INFO|2024-11-25 08:13:53] logging.py:157 >> {'loss': 0.2262, 'learning_rate': 4.9775e-06, 'epoch': 0.15}
[INFO|2024-11-25 08:14:13] logging.py:157 >> {'loss': 0.2650, 'learning_rate': 4.9767e-06, 'epoch': 0.15}
[INFO|2024-11-25 08:14:34] logging.py:157 >> {'loss': 0.3004, 'learning_rate': 4.9759e-06, 'epoch': 0.15}
[INFO|2024-11-25 08:14:55] logging.py:157 >> {'loss': 0.3076, 'learning_rate': 4.9752e-06, 'epoch': 0.15}
[INFO|2024-11-25 08:15:15] logging.py:157 >> {'loss': 0.2370, 'learning_rate': 4.9744e-06, 'epoch': 0.16}
[INFO|2024-11-25 08:15:36] logging.py:157 >> {'loss': 0.3886, 'learning_rate': 4.9736e-06, 'epoch': 0.16}
[INFO|2024-11-25 08:15:57] logging.py:157 >> {'loss': 0.4216, 'learning_rate': 4.9727e-06, 'epoch': 0.16}
[INFO|2024-11-25 08:16:17] logging.py:157 >> {'loss': 0.2869, 'learning_rate': 4.9719e-06, 'epoch': 0.16}
[INFO|2024-11-25 08:16:40] logging.py:157 >> {'loss': 0.2688, 'learning_rate': 4.9711e-06, 'epoch': 0.17}
[INFO|2024-11-25 08:17:01] logging.py:157 >> {'loss': 0.3894, 'learning_rate': 4.9702e-06, 'epoch': 0.17}
[INFO|2024-11-25 08:17:22] logging.py:157 >> {'loss': 0.3129, 'learning_rate': 4.9694e-06, 'epoch': 0.17}
[INFO|2024-11-25 08:17:43] logging.py:157 >> {'loss': 0.3220, 'learning_rate': 4.9685e-06, 'epoch': 0.17}
[INFO|2024-11-25 08:18:03] logging.py:157 >> {'loss': 0.3069, 'learning_rate': 4.9676e-06, 'epoch': 0.17}
[INFO|2024-11-25 08:18:26] logging.py:157 >> {'loss': 0.3893, 'learning_rate': 4.9667e-06, 'epoch': 0.18}
[INFO|2024-11-25 08:18:46] logging.py:157 >> {'loss': 0.3198, 'learning_rate': 4.9658e-06, 'epoch': 0.18}
[INFO|2024-11-25 08:19:06] logging.py:157 >> {'loss': 0.3547, 'learning_rate': 4.9648e-06, 'epoch': 0.18}
[INFO|2024-11-25 08:19:27] logging.py:157 >> {'loss': 0.2338, 'learning_rate': 4.9639e-06, 'epoch': 0.18}
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[INFO|2024-11-25 13:11:06] logging.py:157 >> {'loss': 0.2032, 'learning_rate': 1.3898e-06, 'epoch': 1.95}
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[INFO|2024-11-25 13:12:50] logging.py:157 >> {'loss': 0.1723, 'learning_rate': 1.3648e-06, 'epoch': 1.96}
[INFO|2024-11-25 13:13:12] logging.py:157 >> {'loss': 0.1485, 'learning_rate': 1.3598e-06, 'epoch': 1.96}
[INFO|2024-11-25 13:13:33] logging.py:157 >> {'loss': 0.1481, 'learning_rate': 1.3548e-06, 'epoch': 1.96}
[INFO|2024-11-25 13:13:54] logging.py:157 >> {'loss': 0.2583, 'learning_rate': 1.3498e-06, 'epoch': 1.96}
[INFO|2024-11-25 13:14:16] logging.py:157 >> {'loss': 0.2165, 'learning_rate': 1.3449e-06, 'epoch': 1.96}
[INFO|2024-11-25 13:14:37] logging.py:157 >> {'loss': 0.1807, 'learning_rate': 1.3399e-06, 'epoch': 1.97}
[INFO|2024-11-25 13:14:58] logging.py:157 >> {'loss': 0.2490, 'learning_rate': 1.3350e-06, 'epoch': 1.97}
[INFO|2024-11-25 13:15:19] logging.py:157 >> {'loss': 0.1337, 'learning_rate': 1.3300e-06, 'epoch': 1.97}
[INFO|2024-11-25 13:15:40] logging.py:157 >> {'loss': 0.2563, 'learning_rate': 1.3251e-06, 'epoch': 1.97}
[INFO|2024-11-25 13:16:01] logging.py:157 >> {'loss': 0.2068, 'learning_rate': 1.3201e-06, 'epoch': 1.97}
[INFO|2024-11-25 13:16:22] logging.py:157 >> {'loss': 0.1813, 'learning_rate': 1.3152e-06, 'epoch': 1.98}
[INFO|2024-11-25 13:16:42] logging.py:157 >> {'loss': 0.2077, 'learning_rate': 1.3103e-06, 'epoch': 1.98}
[INFO|2024-11-25 13:17:03] logging.py:157 >> {'loss': 0.1782, 'learning_rate': 1.3053e-06, 'epoch': 1.98}
[INFO|2024-11-25 13:17:25] logging.py:157 >> {'loss': 0.2884, 'learning_rate': 1.3004e-06, 'epoch': 1.98}
[INFO|2024-11-25 13:17:46] logging.py:157 >> {'loss': 0.1920, 'learning_rate': 1.2955e-06, 'epoch': 1.99}
[INFO|2024-11-25 13:18:07] logging.py:157 >> {'loss': 0.1134, 'learning_rate': 1.2906e-06, 'epoch': 1.99}
[INFO|2024-11-25 13:18:29] logging.py:157 >> {'loss': 0.1924, 'learning_rate': 1.2857e-06, 'epoch': 1.99}
[INFO|2024-11-25 13:18:49] logging.py:157 >> {'loss': 0.2068, 'learning_rate': 1.2808e-06, 'epoch': 1.99}
[INFO|2024-11-25 13:19:11] logging.py:157 >> {'loss': 0.1122, 'learning_rate': 1.2759e-06, 'epoch': 1.99}
[INFO|2024-11-25 13:19:32] logging.py:157 >> {'loss': 0.2615, 'learning_rate': 1.2711e-06, 'epoch': 2.00}
[INFO|2024-11-25 13:19:53] logging.py:157 >> {'loss': 0.1196, 'learning_rate': 1.2662e-06, 'epoch': 2.00}
[INFO|2024-11-25 13:20:14] logging.py:157 >> {'loss': 0.2324, 'learning_rate': 1.2613e-06, 'epoch': 2.00}
[INFO|2024-11-25 13:20:35] logging.py:157 >> {'loss': 0.1671, 'learning_rate': 1.2565e-06, 'epoch': 2.00}
[INFO|2024-11-25 13:20:55] logging.py:157 >> {'loss': 0.1219, 'learning_rate': 1.2516e-06, 'epoch': 2.01}
[INFO|2024-11-25 13:21:17] logging.py:157 >> {'loss': 0.1258, 'learning_rate': 1.2468e-06, 'epoch': 2.01}
[INFO|2024-11-25 13:21:39] logging.py:157 >> {'loss': 0.2731, 'learning_rate': 1.2419e-06, 'epoch': 2.01}
[INFO|2024-11-25 13:21:59] logging.py:157 >> {'loss': 0.1510, 'learning_rate': 1.2371e-06, 'epoch': 2.01}
[INFO|2024-11-25 13:22:20] logging.py:157 >> {'loss': 0.1870, 'learning_rate': 1.2323e-06, 'epoch': 2.01}
[INFO|2024-11-25 13:22:41] logging.py:157 >> {'loss': 0.1094, 'learning_rate': 1.2274e-06, 'epoch': 2.02}
[INFO|2024-11-25 13:23:02] logging.py:157 >> {'loss': 0.2884, 'learning_rate': 1.2226e-06, 'epoch': 2.02}
[INFO|2024-11-25 13:23:22] logging.py:157 >> {'loss': 0.1166, 'learning_rate': 1.2178e-06, 'epoch': 2.02}
[INFO|2024-11-25 13:23:43] logging.py:157 >> {'loss': 0.2639, 'learning_rate': 1.2130e-06, 'epoch': 2.02}
[INFO|2024-11-25 13:24:04] logging.py:157 >> {'loss': 0.2392, 'learning_rate': 1.2082e-06, 'epoch': 2.02}
[INFO|2024-11-25 13:24:23] logging.py:157 >> {'loss': 0.1054, 'learning_rate': 1.2034e-06, 'epoch': 2.03}
[INFO|2024-11-25 13:24:44] logging.py:157 >> {'loss': 0.2579, 'learning_rate': 1.1986e-06, 'epoch': 2.03}
[INFO|2024-11-25 13:25:05] logging.py:157 >> {'loss': 0.1962, 'learning_rate': 1.1939e-06, 'epoch': 2.03}
[INFO|2024-11-25 13:25:25] logging.py:157 >> {'loss': 0.1390, 'learning_rate': 1.1891e-06, 'epoch': 2.03}
[INFO|2024-11-25 13:25:46] logging.py:157 >> {'loss': 0.1442, 'learning_rate': 1.1843e-06, 'epoch': 2.03}
[INFO|2024-11-25 13:26:08] logging.py:157 >> {'loss': 0.1862, 'learning_rate': 1.1796e-06, 'epoch': 2.04}
[INFO|2024-11-25 13:26:28] logging.py:157 >> {'loss': 0.1870, 'learning_rate': 1.1748e-06, 'epoch': 2.04}
[INFO|2024-11-25 13:26:48] logging.py:157 >> {'loss': 0.1043, 'learning_rate': 1.1701e-06, 'epoch': 2.04}
[INFO|2024-11-25 13:27:10] logging.py:157 >> {'loss': 0.1359, 'learning_rate': 1.1654e-06, 'epoch': 2.04}
[INFO|2024-11-25 13:27:30] logging.py:157 >> {'loss': 0.1808, 'learning_rate': 1.1606e-06, 'epoch': 2.05}
[INFO|2024-11-25 13:27:51] logging.py:157 >> {'loss': 0.1454, 'learning_rate': 1.1559e-06, 'epoch': 2.05}
[INFO|2024-11-25 13:28:11] logging.py:157 >> {'loss': 0.1273, 'learning_rate': 1.1512e-06, 'epoch': 2.05}
[INFO|2024-11-25 13:28:32] logging.py:157 >> {'loss': 0.1516, 'learning_rate': 1.1465e-06, 'epoch': 2.05}
[INFO|2024-11-25 13:28:54] logging.py:157 >> {'loss': 0.2406, 'learning_rate': 1.1418e-06, 'epoch': 2.05}
[INFO|2024-11-25 13:29:14] logging.py:157 >> {'loss': 0.2046, 'learning_rate': 1.1371e-06, 'epoch': 2.06}
[INFO|2024-11-25 13:29:34] logging.py:157 >> {'loss': 0.1645, 'learning_rate': 1.1324e-06, 'epoch': 2.06}
[INFO|2024-11-25 13:29:54] logging.py:157 >> {'loss': 0.1562, 'learning_rate': 1.1277e-06, 'epoch': 2.06}
[INFO|2024-11-25 13:30:15] logging.py:157 >> {'loss': 0.1089, 'learning_rate': 1.1230e-06, 'epoch': 2.06}
[INFO|2024-11-25 13:30:37] logging.py:157 >> {'loss': 0.2160, 'learning_rate': 1.1184e-06, 'epoch': 2.06}
[INFO|2024-11-25 13:30:57] logging.py:157 >> {'loss': 0.0965, 'learning_rate': 1.1137e-06, 'epoch': 2.07}
[INFO|2024-11-25 13:31:18] logging.py:157 >> {'loss': 0.2348, 'learning_rate': 1.1090e-06, 'epoch': 2.07}
[INFO|2024-11-25 13:31:39] logging.py:157 >> {'loss': 0.1252, 'learning_rate': 1.1044e-06, 'epoch': 2.07}
[INFO|2024-11-25 13:32:00] logging.py:157 >> {'loss': 0.2280, 'learning_rate': 1.0997e-06, 'epoch': 2.07}
[INFO|2024-11-25 13:32:20] logging.py:157 >> {'loss': 0.1241, 'learning_rate': 1.0951e-06, 'epoch': 2.08}
[INFO|2024-11-25 13:32:42] logging.py:157 >> {'loss': 0.1477, 'learning_rate': 1.0905e-06, 'epoch': 2.08}
[INFO|2024-11-25 13:33:03] logging.py:157 >> {'loss': 0.1195, 'learning_rate': 1.0859e-06, 'epoch': 2.08}
[INFO|2024-11-25 13:33:24] logging.py:157 >> {'loss': 0.1273, 'learning_rate': 1.0813e-06, 'epoch': 2.08}
[INFO|2024-11-25 13:33:46] logging.py:157 >> {'loss': 0.1584, 'learning_rate': 1.0767e-06, 'epoch': 2.08}
[INFO|2024-11-25 13:34:07] logging.py:157 >> {'loss': 0.1586, 'learning_rate': 1.0721e-06, 'epoch': 2.09}
[INFO|2024-11-25 13:34:27] logging.py:157 >> {'loss': 0.1341, 'learning_rate': 1.0675e-06, 'epoch': 2.09}
[INFO|2024-11-25 13:34:48] logging.py:157 >> {'loss': 0.1727, 'learning_rate': 1.0629e-06, 'epoch': 2.09}
[INFO|2024-11-25 13:35:08] logging.py:157 >> {'loss': 0.1506, 'learning_rate': 1.0583e-06, 'epoch': 2.09}
[INFO|2024-11-25 13:35:30] logging.py:157 >> {'loss': 0.1112, 'learning_rate': 1.0537e-06, 'epoch': 2.09}
[INFO|2024-11-25 13:35:50] logging.py:157 >> {'loss': 0.2002, 'learning_rate': 1.0492e-06, 'epoch': 2.10}
[INFO|2024-11-25 13:36:11] logging.py:157 >> {'loss': 0.2054, 'learning_rate': 1.0446e-06, 'epoch': 2.10}
[INFO|2024-11-25 13:36:32] logging.py:157 >> {'loss': 0.1530, 'learning_rate': 1.0401e-06, 'epoch': 2.10}
[INFO|2024-11-25 13:36:52] logging.py:157 >> {'loss': 0.1552, 'learning_rate': 1.0355e-06, 'epoch': 2.10}
[INFO|2024-11-25 13:37:13] logging.py:157 >> {'loss': 0.2001, 'learning_rate': 1.0310e-06, 'epoch': 2.10}
[INFO|2024-11-25 13:37:34] logging.py:157 >> {'loss': 0.1307, 'learning_rate': 1.0265e-06, 'epoch': 2.11}
[INFO|2024-11-25 13:37:54] logging.py:157 >> {'loss': 0.1668, 'learning_rate': 1.0219e-06, 'epoch': 2.11}
[INFO|2024-11-25 13:38:15] logging.py:157 >> {'loss': 0.1635, 'learning_rate': 1.0174e-06, 'epoch': 2.11}
[INFO|2024-11-25 13:38:37] logging.py:157 >> {'loss': 0.2443, 'learning_rate': 1.0129e-06, 'epoch': 2.11}
[INFO|2024-11-25 13:38:58] logging.py:157 >> {'loss': 0.1109, 'learning_rate': 1.0084e-06, 'epoch': 2.12}
[INFO|2024-11-25 13:39:18] logging.py:157 >> {'loss': 0.1842, 'learning_rate': 1.0039e-06, 'epoch': 2.12}
[INFO|2024-11-25 13:39:39] logging.py:157 >> {'loss': 0.1828, 'learning_rate': 9.9946e-07, 'epoch': 2.12}
[INFO|2024-11-25 13:40:00] logging.py:157 >> {'loss': 0.1531, 'learning_rate': 9.9499e-07, 'epoch': 2.12}
[INFO|2024-11-25 13:40:08] trainer.py:3801 >> Saving model checkpoint to saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/checkpoint-1000
[INFO|2024-11-25 13:40:08] configuration_utils.py:414 >> Configuration saved in saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/checkpoint-1000/config.json
[INFO|2024-11-25 13:40:08] configuration_utils.py:865 >> Configuration saved in saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/checkpoint-1000/generation_config.json
[INFO|2024-11-25 13:40:24] modeling_utils.py:3043 >> 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/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/checkpoint-1000/model.safetensors.index.json.
[INFO|2024-11-25 13:40:24] tokenization_utils_base.py:2646 >> tokenizer config file saved in saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/checkpoint-1000/tokenizer_config.json
[INFO|2024-11-25 13:40:24] tokenization_utils_base.py:2655 >> Special tokens file saved in saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/checkpoint-1000/special_tokens_map.json
[INFO|2024-11-25 13:41:52] logging.py:157 >> {'loss': 0.1289, 'learning_rate': 9.9052e-07, 'epoch': 2.12}
[INFO|2024-11-25 13:42:14] logging.py:157 >> {'loss': 0.1114, 'learning_rate': 9.8607e-07, 'epoch': 2.13}
[INFO|2024-11-25 13:42:35] logging.py:157 >> {'loss': 0.1902, 'learning_rate': 9.8161e-07, 'epoch': 2.13}
[INFO|2024-11-25 13:42:56] logging.py:157 >> {'loss': 0.1395, 'learning_rate': 9.7717e-07, 'epoch': 2.13}
[INFO|2024-11-25 13:43:17] logging.py:157 >> {'loss': 0.1410, 'learning_rate': 9.7274e-07, 'epoch': 2.13}
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[INFO|2024-11-25 15:31:45] logging.py:157 >> {'loss': 0.1889, 'learning_rate': 5.7539e-08, 'epoch': 2.79}
[INFO|2024-11-25 15:32:06] logging.py:157 >> {'loss': 0.2010, 'learning_rate': 5.6351e-08, 'epoch': 2.80}
[INFO|2024-11-25 15:32:26] logging.py:157 >> {'loss': 0.1615, 'learning_rate': 5.5175e-08, 'epoch': 2.80}
[INFO|2024-11-25 15:32:47] logging.py:157 >> {'loss': 0.1195, 'learning_rate': 5.4012e-08, 'epoch': 2.80}
[INFO|2024-11-25 15:33:09] logging.py:157 >> {'loss': 0.1593, 'learning_rate': 5.2861e-08, 'epoch': 2.80}
[INFO|2024-11-25 15:33:29] logging.py:157 >> {'loss': 0.0893, 'learning_rate': 5.1722e-08, 'epoch': 2.80}
[INFO|2024-11-25 15:33:49] logging.py:157 >> {'loss': 0.2956, 'learning_rate': 5.0595e-08, 'epoch': 2.81}
[INFO|2024-11-25 15:34:11] logging.py:157 >> {'loss': 0.1717, 'learning_rate': 4.9481e-08, 'epoch': 2.81}
[INFO|2024-11-25 15:34:32] logging.py:157 >> {'loss': 0.0977, 'learning_rate': 4.8379e-08, 'epoch': 2.81}
[INFO|2024-11-25 15:34:52] logging.py:157 >> {'loss': 0.1553, 'learning_rate': 4.7289e-08, 'epoch': 2.81}
[INFO|2024-11-25 15:35:12] logging.py:157 >> {'loss': 0.1686, 'learning_rate': 4.6211e-08, 'epoch': 2.82}
[INFO|2024-11-25 15:35:33] logging.py:157 >> {'loss': 0.1846, 'learning_rate': 4.5146e-08, 'epoch': 2.82}
[INFO|2024-11-25 15:35:54] logging.py:157 >> {'loss': 0.1363, 'learning_rate': 4.4093e-08, 'epoch': 2.82}
[INFO|2024-11-25 15:36:14] logging.py:157 >> {'loss': 0.1339, 'learning_rate': 4.3053e-08, 'epoch': 2.82}
[INFO|2024-11-25 15:36:36] logging.py:157 >> {'loss': 0.1288, 'learning_rate': 4.2024e-08, 'epoch': 2.82}
[INFO|2024-11-25 15:36:58] logging.py:157 >> {'loss': 0.1397, 'learning_rate': 4.1008e-08, 'epoch': 2.83}
[INFO|2024-11-25 15:37:18] logging.py:157 >> {'loss': 0.1248, 'learning_rate': 4.0005e-08, 'epoch': 2.83}
[INFO|2024-11-25 15:37:39] logging.py:157 >> {'loss': 0.1981, 'learning_rate': 3.9014e-08, 'epoch': 2.83}
[INFO|2024-11-25 15:38:00] logging.py:157 >> {'loss': 0.1387, 'learning_rate': 3.8035e-08, 'epoch': 2.83}
[INFO|2024-11-25 15:38:20] logging.py:157 >> {'loss': 0.1013, 'learning_rate': 3.7068e-08, 'epoch': 2.83}
[INFO|2024-11-25 15:38:40] logging.py:157 >> {'loss': 0.2936, 'learning_rate': 3.6114e-08, 'epoch': 2.84}
[INFO|2024-11-25 15:39:03] logging.py:157 >> {'loss': 0.1551, 'learning_rate': 3.5172e-08, 'epoch': 2.84}
[INFO|2024-11-25 15:39:24] logging.py:157 >> {'loss': 0.1314, 'learning_rate': 3.4242e-08, 'epoch': 2.84}
[INFO|2024-11-25 15:39:43] logging.py:157 >> {'loss': 0.1936, 'learning_rate': 3.3325e-08, 'epoch': 2.84}
[INFO|2024-11-25 15:40:04] logging.py:157 >> {'loss': 0.1696, 'learning_rate': 3.2420e-08, 'epoch': 2.84}
[INFO|2024-11-25 15:40:24] logging.py:157 >> {'loss': 0.0762, 'learning_rate': 3.1528e-08, 'epoch': 2.85}
[INFO|2024-11-25 15:40:46] logging.py:157 >> {'loss': 0.1341, 'learning_rate': 3.0648e-08, 'epoch': 2.85}
[INFO|2024-11-25 15:41:06] logging.py:157 >> {'loss': 0.1482, 'learning_rate': 2.9780e-08, 'epoch': 2.85}
[INFO|2024-11-25 15:41:27] logging.py:157 >> {'loss': 0.1360, 'learning_rate': 2.8925e-08, 'epoch': 2.85}
[INFO|2024-11-25 15:41:48] logging.py:157 >> {'loss': 0.1296, 'learning_rate': 2.8082e-08, 'epoch': 2.86}
[INFO|2024-11-25 15:42:08] logging.py:157 >> {'loss': 0.1119, 'learning_rate': 2.7252e-08, 'epoch': 2.86}
[INFO|2024-11-25 15:42:28] logging.py:157 >> {'loss': 0.1892, 'learning_rate': 2.6433e-08, 'epoch': 2.86}
[INFO|2024-11-25 15:42:50] logging.py:157 >> {'loss': 0.1666, 'learning_rate': 2.5628e-08, 'epoch': 2.86}
[INFO|2024-11-25 15:43:10] logging.py:157 >> {'loss': 0.1364, 'learning_rate': 2.4834e-08, 'epoch': 2.86}
[INFO|2024-11-25 15:43:31] logging.py:157 >> {'loss': 0.1658, 'learning_rate': 2.4054e-08, 'epoch': 2.87}
[INFO|2024-11-25 15:43:52] logging.py:157 >> {'loss': 0.1677, 'learning_rate': 2.3285e-08, 'epoch': 2.87}
[INFO|2024-11-25 15:44:14] logging.py:157 >> {'loss': 0.1026, 'learning_rate': 2.2529e-08, 'epoch': 2.87}
[INFO|2024-11-25 15:44:35] logging.py:157 >> {'loss': 0.1761, 'learning_rate': 2.1785e-08, 'epoch': 2.87}
[INFO|2024-11-25 15:44:56] logging.py:157 >> {'loss': 0.2169, 'learning_rate': 2.1054e-08, 'epoch': 2.87}
[INFO|2024-11-25 15:45:18] logging.py:157 >> {'loss': 0.1990, 'learning_rate': 2.0335e-08, 'epoch': 2.88}
[INFO|2024-11-25 15:45:39] logging.py:157 >> {'loss': 0.1348, 'learning_rate': 1.9629e-08, 'epoch': 2.88}
[INFO|2024-11-25 15:46:00] logging.py:157 >> {'loss': 0.0994, 'learning_rate': 1.8935e-08, 'epoch': 2.88}
[INFO|2024-11-25 15:46:21] logging.py:157 >> {'loss': 0.1815, 'learning_rate': 1.8254e-08, 'epoch': 2.88}
[INFO|2024-11-25 15:46:42] logging.py:157 >> {'loss': 0.1956, 'learning_rate': 1.7585e-08, 'epoch': 2.89}
[INFO|2024-11-25 15:47:03] logging.py:157 >> {'loss': 0.1832, 'learning_rate': 1.6928e-08, 'epoch': 2.89}
[INFO|2024-11-25 15:47:23] logging.py:157 >> {'loss': 0.2045, 'learning_rate': 1.6284e-08, 'epoch': 2.89}
[INFO|2024-11-25 15:47:44] logging.py:157 >> {'loss': 0.1563, 'learning_rate': 1.5652e-08, 'epoch': 2.89}
[INFO|2024-11-25 15:48:04] logging.py:157 >> {'loss': 0.1395, 'learning_rate': 1.5033e-08, 'epoch': 2.89}
[INFO|2024-11-25 15:48:26] logging.py:157 >> {'loss': 0.1354, 'learning_rate': 1.4426e-08, 'epoch': 2.90}
[INFO|2024-11-25 15:48:47] logging.py:157 >> {'loss': 0.1807, 'learning_rate': 1.3832e-08, 'epoch': 2.90}
[INFO|2024-11-25 15:49:08] logging.py:157 >> {'loss': 0.2193, 'learning_rate': 1.3250e-08, 'epoch': 2.90}
[INFO|2024-11-25 15:49:29] logging.py:157 >> {'loss': 0.1427, 'learning_rate': 1.2681e-08, 'epoch': 2.90}
[INFO|2024-11-25 15:49:49] logging.py:157 >> {'loss': 0.1666, 'learning_rate': 1.2124e-08, 'epoch': 2.90}
[INFO|2024-11-25 15:50:10] logging.py:157 >> {'loss': 0.1087, 'learning_rate': 1.1580e-08, 'epoch': 2.91}
[INFO|2024-11-25 15:50:31] logging.py:157 >> {'loss': 0.1042, 'learning_rate': 1.1048e-08, 'epoch': 2.91}
[INFO|2024-11-25 15:50:51] logging.py:157 >> {'loss': 0.1230, 'learning_rate': 1.0528e-08, 'epoch': 2.91}
[INFO|2024-11-25 15:51:13] logging.py:157 >> {'loss': 0.2518, 'learning_rate': 1.0021e-08, 'epoch': 2.91}
[INFO|2024-11-25 15:51:35] logging.py:157 >> {'loss': 0.1938, 'learning_rate': 9.5268e-09, 'epoch': 2.91}
[INFO|2024-11-25 15:51:55] logging.py:157 >> {'loss': 0.1524, 'learning_rate': 9.0448e-09, 'epoch': 2.92}
[INFO|2024-11-25 15:52:17] logging.py:157 >> {'loss': 0.0865, 'learning_rate': 8.5753e-09, 'epoch': 2.92}
[INFO|2024-11-25 15:52:38] logging.py:157 >> {'loss': 0.1245, 'learning_rate': 8.1183e-09, 'epoch': 2.92}
[INFO|2024-11-25 15:52:58] logging.py:157 >> {'loss': 0.1392, 'learning_rate': 7.6738e-09, 'epoch': 2.92}
[INFO|2024-11-25 15:53:20] logging.py:157 >> {'loss': 0.1392, 'learning_rate': 7.2417e-09, 'epoch': 2.93}
[INFO|2024-11-25 15:53:40] logging.py:157 >> {'loss': 0.1728, 'learning_rate': 6.8222e-09, 'epoch': 2.93}
[INFO|2024-11-25 15:54:01] logging.py:157 >> {'loss': 0.1577, 'learning_rate': 6.4152e-09, 'epoch': 2.93}
[INFO|2024-11-25 15:54:22] logging.py:157 >> {'loss': 0.1659, 'learning_rate': 6.0207e-09, 'epoch': 2.93}
[INFO|2024-11-25 15:54:42] logging.py:157 >> {'loss': 0.1507, 'learning_rate': 5.6386e-09, 'epoch': 2.93}
[INFO|2024-11-25 15:55:03] logging.py:157 >> {'loss': 0.1365, 'learning_rate': 5.2691e-09, 'epoch': 2.94}
[INFO|2024-11-25 15:55:24] logging.py:157 >> {'loss': 0.1626, 'learning_rate': 4.9121e-09, 'epoch': 2.94}
[INFO|2024-11-25 15:55:45] logging.py:157 >> {'loss': 0.1482, 'learning_rate': 4.5676e-09, 'epoch': 2.94}
[INFO|2024-11-25 15:56:09] logging.py:157 >> {'loss': 0.1666, 'learning_rate': 4.2356e-09, 'epoch': 2.94}
[INFO|2024-11-25 15:56:32] logging.py:157 >> {'loss': 0.1035, 'learning_rate': 3.9162e-09, 'epoch': 2.94}
[INFO|2024-11-25 15:56:53] logging.py:157 >> {'loss': 0.1345, 'learning_rate': 3.6092e-09, 'epoch': 2.95}
[INFO|2024-11-25 15:57:13] logging.py:157 >> {'loss': 0.1287, 'learning_rate': 3.3148e-09, 'epoch': 2.95}
[INFO|2024-11-25 15:57:34] logging.py:157 >> {'loss': 0.1304, 'learning_rate': 3.0329e-09, 'epoch': 2.95}
[INFO|2024-11-25 15:57:55] logging.py:157 >> {'loss': 0.1966, 'learning_rate': 2.7635e-09, 'epoch': 2.95}
[INFO|2024-11-25 15:58:16] logging.py:157 >> {'loss': 0.1600, 'learning_rate': 2.5066e-09, 'epoch': 2.96}
[INFO|2024-11-25 15:58:39] logging.py:157 >> {'loss': 0.2442, 'learning_rate': 2.2622e-09, 'epoch': 2.96}
[INFO|2024-11-25 15:58:59] logging.py:157 >> {'loss': 0.1084, 'learning_rate': 2.0304e-09, 'epoch': 2.96}
[INFO|2024-11-25 15:59:20] logging.py:157 >> {'loss': 0.1805, 'learning_rate': 1.8111e-09, 'epoch': 2.96}
[INFO|2024-11-25 15:59:40] logging.py:157 >> {'loss': 0.1576, 'learning_rate': 1.6043e-09, 'epoch': 2.96}
[INFO|2024-11-25 16:00:02] logging.py:157 >> {'loss': 0.1739, 'learning_rate': 1.4101e-09, 'epoch': 2.97}
[INFO|2024-11-25 16:00:23] logging.py:157 >> {'loss': 0.1755, 'learning_rate': 1.2283e-09, 'epoch': 2.97}
[INFO|2024-11-25 16:00:43] logging.py:157 >> {'loss': 0.1123, 'learning_rate': 1.0591e-09, 'epoch': 2.97}
[INFO|2024-11-25 16:01:05] logging.py:157 >> {'loss': 0.1952, 'learning_rate': 9.0247e-10, 'epoch': 2.97}
[INFO|2024-11-25 16:01:26] logging.py:157 >> {'loss': 0.1802, 'learning_rate': 7.5833e-10, 'epoch': 2.97}
[INFO|2024-11-25 16:01:46] logging.py:157 >> {'loss': 0.1862, 'learning_rate': 6.2672e-10, 'epoch': 2.98}
[INFO|2024-11-25 16:02:07] logging.py:157 >> {'loss': 0.1186, 'learning_rate': 5.0765e-10, 'epoch': 2.98}
[INFO|2024-11-25 16:02:28] logging.py:157 >> {'loss': 0.2020, 'learning_rate': 4.0111e-10, 'epoch': 2.98}
[INFO|2024-11-25 16:02:48] logging.py:157 >> {'loss': 0.1106, 'learning_rate': 3.0710e-10, 'epoch': 2.98}
[INFO|2024-11-25 16:03:09] logging.py:157 >> {'loss': 0.2274, 'learning_rate': 2.2563e-10, 'epoch': 2.98}
[INFO|2024-11-25 16:03:29] logging.py:157 >> {'loss': 0.0980, 'learning_rate': 1.5669e-10, 'epoch': 2.99}
[INFO|2024-11-25 16:03:49] logging.py:157 >> {'loss': 0.1817, 'learning_rate': 1.0028e-10, 'epoch': 2.99}
[INFO|2024-11-25 16:04:11] logging.py:157 >> {'loss': 0.1669, 'learning_rate': 5.6407e-11, 'epoch': 2.99}
[INFO|2024-11-25 16:04:30] logging.py:157 >> {'loss': 0.1413, 'learning_rate': 2.5070e-11, 'epoch': 2.99}
[INFO|2024-11-25 16:04:50] logging.py:157 >> {'loss': 0.3418, 'learning_rate': 6.2675e-12, 'epoch': 3.00}
[INFO|2024-11-25 16:05:11] logging.py:157 >> {'loss': 0.1737, 'learning_rate': 0.0000e+00, 'epoch': 3.00}
[INFO|2024-11-25 16:05:19] trainer.py:3801 >> Saving model checkpoint to saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/checkpoint-1413
[INFO|2024-11-25 16:05:19] configuration_utils.py:414 >> Configuration saved in saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/checkpoint-1413/config.json
[INFO|2024-11-25 16:05:19] configuration_utils.py:865 >> Configuration saved in saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/checkpoint-1413/generation_config.json
[INFO|2024-11-25 16:05:38] modeling_utils.py:3043 >> 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/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/checkpoint-1413/model.safetensors.index.json.
[INFO|2024-11-25 16:05:38] tokenization_utils_base.py:2646 >> tokenizer config file saved in saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/checkpoint-1413/tokenizer_config.json
[INFO|2024-11-25 16:05:38] tokenization_utils_base.py:2655 >> Special tokens file saved in saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/checkpoint-1413/special_tokens_map.json
[INFO|2024-11-25 16:06:37] trainer.py:2584 >>
Training completed. Do not forget to share your model on huggingface.co/models =)
[INFO|2024-11-25 16:06:45] trainer.py:3801 >> Saving model checkpoint to saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41
[INFO|2024-11-25 16:06:45] configuration_utils.py:414 >> Configuration saved in saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/config.json
[INFO|2024-11-25 16:06:45] configuration_utils.py:865 >> Configuration saved in saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/generation_config.json
[INFO|2024-11-25 16:07:17] modeling_utils.py:3043 >> 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/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/model.safetensors.index.json.
[INFO|2024-11-25 16:07:17] tokenization_utils_base.py:2646 >> tokenizer config file saved in saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/tokenizer_config.json
[INFO|2024-11-25 16:07:17] tokenization_utils_base.py:2655 >> Special tokens file saved in saves/Llama-3-8B-Instruct/full/train_2024-11-25-07-46-41/special_tokens_map.json
[WARNING|2024-11-25 16:07:18] logging.py:162 >> No metric eval_loss to plot.
[WARNING|2024-11-25 16:07:18] logging.py:162 >> No metric eval_accuracy to plot.
[INFO|2024-11-25 16:07:18] modelcard.py:449 >> Dropping the following result as it does not have all the necessary fields:
{'task': {'name': 'Causal Language Modeling', 'type': 'text-generation'}}