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[INFO|tokenization_utils_base.py:2024] 2024-01-18 19:25:40,385 >> loading file tokenizer.model |
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[INFO|tokenization_utils_base.py:2024] 2024-01-18 19:25:40,385 >> loading file added_tokens.json |
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[INFO|tokenization_utils_base.py:2024] 2024-01-18 19:25:40,385 >> loading file special_tokens_map.json |
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[INFO|tokenization_utils_base.py:2024] 2024-01-18 19:25:40,385 >> loading file tokenizer_config.json |
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[INFO|tokenization_utils_base.py:2024] 2024-01-18 19:25:40,385 >> loading file tokenizer.json |
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[INFO|configuration_utils.py:737] 2024-01-18 19:25:40,429 >> loading configuration file ./models/LMCocktail-10.7B-v1/config.json |
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[INFO|configuration_utils.py:802] 2024-01-18 19:25:40,430 >> Model config LlamaConfig { |
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"_name_or_path": "./models/LMCocktail-10.7B-v1", |
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"architectures": [ |
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"LlamaForCausalLM" |
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], |
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"attention_bias": false, |
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"attention_dropout": 0.0, |
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"bos_token_id": 1, |
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"eos_token_id": 2, |
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"hidden_act": "silu", |
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"hidden_size": 4096, |
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"initializer_range": 0.02, |
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"intermediate_size": 14336, |
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"max_position_embeddings": 4096, |
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"model_type": "llama", |
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"num_attention_heads": 32, |
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"num_hidden_layers": 48, |
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"num_key_value_heads": 8, |
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"pad_token_id": 2, |
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"pretraining_tp": 1, |
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"rms_norm_eps": 1e-05, |
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"rope_scaling": null, |
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"rope_theta": 10000.0, |
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"tie_word_embeddings": false, |
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"torch_dtype": "float16", |
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"transformers_version": "4.36.2", |
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"use_cache": true, |
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"vocab_size": 32000 |
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} |
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[INFO|modeling_utils.py:3341] 2024-01-18 19:25:40,446 >> loading weights file ./models/LMCocktail-10.7B-v1/model.safetensors.index.json |
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[INFO|modeling_utils.py:1341] 2024-01-18 19:25:40,447 >> Instantiating LlamaForCausalLM model under default dtype torch.float16. |
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[INFO|configuration_utils.py:826] 2024-01-18 19:25:40,447 >> Generate config GenerationConfig { |
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"bos_token_id": 1, |
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"eos_token_id": 2, |
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"pad_token_id": 2 |
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} |
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Loading checkpoint shards: 0%| | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards: 20%|ββ | 1/5 [00:00<00:00, 6.36it/s]
Loading checkpoint shards: 40%|ββββ | 2/5 [00:00<00:00, 6.36it/s]
Loading checkpoint shards: 60%|ββββββ | 3/5 [00:00<00:00, 6.37it/s]
Loading checkpoint shards: 80%|ββββββββ | 4/5 [00:00<00:00, 6.28it/s]
Loading checkpoint shards: 100%|ββββββββββ| 5/5 [00:00<00:00, 6.33it/s]
Loading checkpoint shards: 100%|ββββββββββ| 5/5 [00:00<00:00, 6.33it/s] |
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[INFO|modeling_utils.py:4185] 2024-01-18 19:25:41,404 >> All model checkpoint weights were used when initializing LlamaForCausalLM. |
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[INFO|modeling_utils.py:4193] 2024-01-18 19:25:41,404 >> All the weights of LlamaForCausalLM were initialized from the model checkpoint at ./models/LMCocktail-10.7B-v1. |
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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. |
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[INFO|configuration_utils.py:779] 2024-01-18 19:25:41,407 >> loading configuration file ./models/LMCocktail-10.7B-v1/generation_config.json |
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[INFO|configuration_utils.py:826] 2024-01-18 19:25:41,408 >> Generate config GenerationConfig { |
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"bos_token_id": 1, |
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"eos_token_id": 2, |
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"pad_token_id": 2, |
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"use_cache": false |
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} |
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01/18/2024 19:25:41 - INFO - llmtuner.model.adapter - Fine-tuning method: LoRA |
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01/18/2024 19:25:43 - INFO - llmtuner.model.adapter - Merged 1 adapter(s). |
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01/18/2024 19:25:43 - INFO - llmtuner.model.adapter - Loaded adapter(s): ./models/sft/LMCocktail-10.7B-v1-sft-glaive-function-calling-v2-ep1-lora |
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01/18/2024 19:25:43 - INFO - llmtuner.model.loader - trainable params: 0 || all params: 10731524096 || trainable%: 0.0000 |
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01/18/2024 19:25:43 - INFO - llmtuner.model.loader - This IS expected that the trainable params is 0 if you are using model for inference only. |
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[INFO|configuration_utils.py:483] 2024-01-18 19:25:43,941 >> Configuration saved in ./models/export/LMCocktail-10.7B-v1-sft-glaive-function-calling-v2-ep1/config.json |
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[INFO|configuration_utils.py:594] 2024-01-18 19:25:43,941 >> Configuration saved in ./models/export/LMCocktail-10.7B-v1-sft-glaive-function-calling-v2-ep1/generation_config.json |
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[INFO|modeling_utils.py:2390] 2024-01-18 19:26:02,405 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 5 checkpoint shards. You can find where each parameters has been saved in the index located at ./models/export/LMCocktail-10.7B-v1-sft-glaive-function-calling-v2-ep1/model.safetensors.index.json. |
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[INFO|tokenization_utils_base.py:2432] 2024-01-18 19:26:02,406 >> tokenizer config file saved in ./models/export/LMCocktail-10.7B-v1-sft-glaive-function-calling-v2-ep1/tokenizer_config.json |
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[INFO|tokenization_utils_base.py:2441] 2024-01-18 19:26:02,406 >> Special tokens file saved in ./models/export/LMCocktail-10.7B-v1-sft-glaive-function-calling-v2-ep1/special_tokens_map.json |
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