Model save
Browse files- README.md +56 -0
- adapter_config.json +3 -3
- adapter_model.safetensors +1 -1
- special_tokens_map.json +1 -1
- tokenizer.json +0 -9
- tokenizer_config.json +1 -9
- training_args.bin +1 -1
README.md
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---
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license: llama3
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library_name: peft
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tags:
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- trl
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- sft
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- generated_from_trainer
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base_model: meta-llama/Meta-Llama-3-8B-Instruct
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model-index:
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- name: llama-3-8B-Intruct-ft
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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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# llama-3-8B-Intruct-ft
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset.
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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: 3e-05
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- train_batch_size: 2
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.05
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- training_steps: 128
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- mixed_precision_training: Native AMP
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### Framework versions
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- PEFT 0.11.1
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- Transformers 4.41.2
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- Pytorch 2.1.0.post2+cxx11.abi
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"k_proj",
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"output_proj",
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"v_proj",
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"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "meta-llama/Meta-Llama-3-8B-Instruct",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"output_proj",
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"q_proj",
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"v_proj",
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"k_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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adapter_model.safetensors
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special_tokens_map.json
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "<|eot_id|>"
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}
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tokenizer.json
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"rstrip": false,
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"normalized": false,
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"special": true
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},
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{
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"id": 128256,
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"content": "[PAD]",
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"single_word": false,
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"lstrip": false,
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"rstrip": false,
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"normalized": false,
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"special": true
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],
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"normalizer": null,
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"rstrip": false,
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"normalized": false,
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"special": true
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}
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],
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"normalizer": null,
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tokenizer_config.json
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"128256": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"bos_token": "<|begin_of_text|>",
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"attention_mask"
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],
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "
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"tokenizer_class": "PreTrainedTokenizerFast"
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}
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"bos_token": "<|begin_of_text|>",
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"attention_mask"
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],
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "<|eot_id|>",
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"tokenizer_class": "PreTrainedTokenizerFast"
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}
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training_args.bin
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