| [INFO|configuration_utils.py:731] 2024-09-25 21:54:48,859 >> loading configuration file /mnt/c/checkout/Phi-3.5-mini-instruct/config.json | |
| [INFO|configuration_utils.py:731] 2024-09-25 21:54:48,876 >> loading configuration file /mnt/c/checkout/Phi-3.5-mini-instruct/config.json | |
| [INFO|configuration_utils.py:800] 2024-09-25 21:54:48,877 >> Model config Phi3Config { | |
| "_name_or_path": "/mnt/c/checkout/Phi-3.5-mini-instruct", | |
| "architectures": [ | |
| "Phi3ForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_phi3.Phi3Config", | |
| "AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM" | |
| }, | |
| "bos_token_id": 1, | |
| "embd_pdrop": 0.0, | |
| "eos_token_id": 32000, | |
| "hidden_act": "silu", | |
| "hidden_size": 3072, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 8192, | |
| "max_position_embeddings": 131072, | |
| "model_type": "phi3", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 32, | |
| "original_max_position_embeddings": 4096, | |
| "pad_token_id": 32000, | |
| "resid_pdrop": 0.0, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": { | |
| "long_factor": [ | |
| 1.0800000429153442, | |
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| "short_factor": [ | |
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| ], | |
| "type": "longrope" | |
| }, | |
| "rope_theta": 10000.0, | |
| "sliding_window": 262144, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.44.2", | |
| "use_cache": true, | |
| "vocab_size": 32064 | |
| } | |
| [INFO|tokenization_utils_base.py:2267] 2024-09-25 21:54:48,919 >> loading file tokenizer.model | |
| [INFO|tokenization_utils_base.py:2267] 2024-09-25 21:54:48,919 >> loading file tokenizer.json | |
| [INFO|tokenization_utils_base.py:2267] 2024-09-25 21:54:48,919 >> loading file added_tokens.json | |
| [INFO|tokenization_utils_base.py:2267] 2024-09-25 21:54:48,919 >> loading file special_tokens_map.json | |
| [INFO|tokenization_utils_base.py:2267] 2024-09-25 21:54:48,919 >> loading file tokenizer_config.json | |
| [INFO|tokenization_utils_base.py:2513] 2024-09-25 21:54:48,960 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. | |
| [INFO|configuration_utils.py:731] 2024-09-25 21:54:48,969 >> loading configuration file /mnt/c/checkout/Phi-3.5-mini-instruct/config.json | |
| [INFO|configuration_utils.py:731] 2024-09-25 21:54:48,979 >> loading configuration file /mnt/c/checkout/Phi-3.5-mini-instruct/config.json | |
| [INFO|configuration_utils.py:800] 2024-09-25 21:54:48,979 >> Model config Phi3Config { | |
| "_name_or_path": "/mnt/c/checkout/Phi-3.5-mini-instruct", | |
| "architectures": [ | |
| "Phi3ForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_phi3.Phi3Config", | |
| "AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM" | |
| }, | |
| "bos_token_id": 1, | |
| "embd_pdrop": 0.0, | |
| "eos_token_id": 32000, | |
| "hidden_act": "silu", | |
| "hidden_size": 3072, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 8192, | |
| "max_position_embeddings": 131072, | |
| "model_type": "phi3", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 32, | |
| "original_max_position_embeddings": 4096, | |
| "pad_token_id": 32000, | |
| "resid_pdrop": 0.0, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": { | |
| "long_factor": [ | |
| 1.0800000429153442, | |
| 1.1100000143051147, | |
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| ], | |
| "short_factor": [ | |
| 1.0, | |
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| ], | |
| "type": "longrope" | |
| }, | |
| "rope_theta": 10000.0, | |
| "sliding_window": 262144, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.44.2", | |
| "use_cache": true, | |
| "vocab_size": 32064 | |
| } | |
| [INFO|tokenization_utils_base.py:2267] 2024-09-25 21:54:48,992 >> loading file tokenizer.model | |
| [INFO|tokenization_utils_base.py:2267] 2024-09-25 21:54:48,992 >> loading file tokenizer.json | |
| [INFO|tokenization_utils_base.py:2267] 2024-09-25 21:54:48,993 >> loading file added_tokens.json | |
| [INFO|tokenization_utils_base.py:2267] 2024-09-25 21:54:48,993 >> loading file special_tokens_map.json | |
| [INFO|tokenization_utils_base.py:2267] 2024-09-25 21:54:48,993 >> loading file tokenizer_config.json | |
| [INFO|tokenization_utils_base.py:2513] 2024-09-25 21:54:49,030 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. | |
| [INFO|configuration_utils.py:731] 2024-09-25 21:54:49,791 >> loading configuration file /mnt/c/checkout/Phi-3.5-mini-instruct/config.json | |
| [INFO|configuration_utils.py:731] 2024-09-25 21:54:49,799 >> loading configuration file /mnt/c/checkout/Phi-3.5-mini-instruct/config.json | |
| [INFO|configuration_utils.py:800] 2024-09-25 21:54:49,800 >> Model config Phi3Config { | |
| "_name_or_path": "/mnt/c/checkout/Phi-3.5-mini-instruct", | |
| "architectures": [ | |
| "Phi3ForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_phi3.Phi3Config", | |
| "AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM" | |
| }, | |
| "bos_token_id": 1, | |
| "embd_pdrop": 0.0, | |
| "eos_token_id": 32000, | |
| "hidden_act": "silu", | |
| "hidden_size": 3072, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 8192, | |
| "max_position_embeddings": 131072, | |
| "model_type": "phi3", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 32, | |
| "original_max_position_embeddings": 4096, | |
| "pad_token_id": 32000, | |
| "resid_pdrop": 0.0, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": { | |
| "long_factor": [ | |
| 1.0800000429153442, | |
| 1.1100000143051147, | |
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| "short_factor": [ | |
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| ], | |
| "type": "longrope" | |
| }, | |
| "rope_theta": 10000.0, | |
| "sliding_window": 262144, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.44.2", | |
| "use_cache": true, | |
| "vocab_size": 32064 | |
| } | |
| [WARNING|modeling_phi3.py:62] 2024-09-25 21:54:51,178 >> `flash-attention` package not found, consider installing for better performance: No module named 'flash_attn'. | |
| [WARNING|modeling_phi3.py:66] 2024-09-25 21:54:51,178 >> Current `flash-attention` does not support `window_size`. Either upgrade or use `attn_implementation='eager'`. | |
| [INFO|modeling_utils.py:3675] 2024-09-25 21:54:51,183 >> loading weights file /mnt/c/checkout/Phi-3.5-mini-instruct/model.safetensors.index.json | |
| [INFO|modeling_utils.py:1606] 2024-09-25 21:54:51,191 >> Instantiating Phi3ForCausalLM model under default dtype torch.bfloat16. | |
| [INFO|configuration_utils.py:1038] 2024-09-25 21:54:51,191 >> Generate config GenerationConfig { | |
| "bos_token_id": 1, | |
| "eos_token_id": 32000, | |
| "pad_token_id": 32000 | |
| } | |
| [INFO|modeling_utils.py:4507] 2024-09-25 21:56:43,132 >> All model checkpoint weights were used when initializing Phi3ForCausalLM. | |
| [INFO|modeling_utils.py:4515] 2024-09-25 21:56:43,132 >> All the weights of Phi3ForCausalLM were initialized from the model checkpoint at /mnt/c/checkout/Phi-3.5-mini-instruct. | |
| If your task is similar to the task the model of the checkpoint was trained on, you can already use Phi3ForCausalLM for predictions without further training. | |
| [INFO|configuration_utils.py:991] 2024-09-25 21:56:43,142 >> loading configuration file /mnt/c/checkout/Phi-3.5-mini-instruct/generation_config.json | |
| [INFO|configuration_utils.py:1038] 2024-09-25 21:56:43,142 >> Generate config GenerationConfig { | |
| "bos_token_id": 1, | |
| "eos_token_id": [ | |
| 32007, | |
| 32001, | |
| 32000 | |
| ], | |
| "pad_token_id": 32000 | |
| } | |
| [INFO|trainer.py:648] 2024-09-25 21:56:43,208 >> Using auto half precision backend | |
| [INFO|trainer.py:2134] 2024-09-25 21:57:01,081 >> ***** Running training ***** | |
| [INFO|trainer.py:2135] 2024-09-25 21:57:01,081 >> Num examples = 3,900 | |
| [INFO|trainer.py:2136] 2024-09-25 21:57:01,081 >> Num Epochs = 32 | |
| [INFO|trainer.py:2137] 2024-09-25 21:57:01,081 >> Instantaneous batch size per device = 4 | |
| [INFO|trainer.py:2140] 2024-09-25 21:57:01,081 >> Total train batch size (w. parallel, distributed & accumulation) = 16 | |
| [INFO|trainer.py:2141] 2024-09-25 21:57:01,081 >> Gradient Accumulation steps = 4 | |
| [INFO|trainer.py:2142] 2024-09-25 21:57:01,081 >> Total optimization steps = 7,776 | |
| [INFO|trainer.py:2143] 2024-09-25 21:57:01,082 >> Number of trainable parameters = 113,252,352 | |
| [WARNING|logging.py:328] 2024-09-25 21:57:01,353 >> You are not running the flash-attention implementation, expect numerical differences. | |
| [INFO|trainer.py:3503] 2024-09-26 01:55:14,826 >> Saving model checkpoint to saves/Custom/full/SpecAI/checkpoint-2000 | |
| [INFO|configuration_utils.py:472] 2024-09-26 01:55:14,876 >> Configuration saved in saves/Custom/full/SpecAI/checkpoint-2000/config.json | |
| [INFO|configuration_utils.py:807] 2024-09-26 01:55:14,882 >> Configuration saved in saves/Custom/full/SpecAI/checkpoint-2000/generation_config.json | |
| [INFO|modeling_utils.py:2807] 2024-09-26 01:55:31,164 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 2 checkpoint shards. You can find where each parameters has been saved in the index located at saves/Custom/full/SpecAI/checkpoint-2000/model.safetensors.index.json. | |
| [INFO|tokenization_utils_base.py:2684] 2024-09-26 01:55:31,171 >> tokenizer config file saved in saves/Custom/full/SpecAI/checkpoint-2000/tokenizer_config.json | |
| [INFO|tokenization_utils_base.py:2693] 2024-09-26 01:55:31,175 >> Special tokens file saved in saves/Custom/full/SpecAI/checkpoint-2000/special_tokens_map.json | |
| [INFO|trainer.py:3503] 2024-09-26 06:01:21,589 >> Saving model checkpoint to saves/Custom/full/SpecAI/checkpoint-4000 | |
| [INFO|configuration_utils.py:472] 2024-09-26 06:01:21,634 >> Configuration saved in saves/Custom/full/SpecAI/checkpoint-4000/config.json | |
| [INFO|configuration_utils.py:807] 2024-09-26 06:01:21,639 >> Configuration saved in saves/Custom/full/SpecAI/checkpoint-4000/generation_config.json | |
| [INFO|modeling_utils.py:2807] 2024-09-26 06:01:33,186 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 2 checkpoint shards. You can find where each parameters has been saved in the index located at saves/Custom/full/SpecAI/checkpoint-4000/model.safetensors.index.json. | |
| [INFO|tokenization_utils_base.py:2684] 2024-09-26 06:01:33,193 >> tokenizer config file saved in saves/Custom/full/SpecAI/checkpoint-4000/tokenizer_config.json | |
| [INFO|tokenization_utils_base.py:2693] 2024-09-26 06:01:33,196 >> Special tokens file saved in saves/Custom/full/SpecAI/checkpoint-4000/special_tokens_map.json | |
| [INFO|trainer.py:2394] 2024-09-26 07:57:18,192 >> | |
| Training completed. Do not forget to share your model on huggingface.co/models =) | |
| [INFO|trainer.py:3503] 2024-09-26 07:57:18,202 >> Saving model checkpoint to saves/Custom/full/SpecAI | |
| [INFO|configuration_utils.py:472] 2024-09-26 07:57:18,244 >> Configuration saved in saves/Custom/full/SpecAI/config.json | |
| [INFO|configuration_utils.py:807] 2024-09-26 07:57:18,247 >> Configuration saved in saves/Custom/full/SpecAI/generation_config.json | |
| [INFO|modeling_utils.py:2807] 2024-09-26 07:57:29,353 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 2 checkpoint shards. You can find where each parameters has been saved in the index located at saves/Custom/full/SpecAI/model.safetensors.index.json. | |
| [INFO|tokenization_utils_base.py:2684] 2024-09-26 07:57:29,357 >> tokenizer config file saved in saves/Custom/full/SpecAI/tokenizer_config.json | |
| [INFO|tokenization_utils_base.py:2693] 2024-09-26 07:57:29,359 >> Special tokens file saved in saves/Custom/full/SpecAI/special_tokens_map.json | |
| [INFO|modelcard.py:449] 2024-09-26 07:57:29,626 >> Dropping the following result as it does not have all the necessary fields: | |
| {'task': {'name': 'Causal Language Modeling', 'type': 'text-generation'}} | |