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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: TheBloke/Mistral-7B-Instruct-v0.1-GPTQ |
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model-index: |
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- name: mistral-finetuned-samsum |
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results: [] |
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pipeline_tag: text-generation |
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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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# mistral-finetuned-samsum |
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This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.1-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.1-GPTQ) on the None 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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The following `bitsandbytes` quantization config was used during training: |
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- quant_method: gptq |
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- bits: 4 |
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- tokenizer: None |
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- dataset: None |
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- group_size: 128 |
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- damp_percent: 0.1 |
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- desc_act: True |
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- sym: True |
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- true_sequential: True |
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- use_cuda_fp16: False |
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- model_seqlen: None |
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- block_name_to_quantize: None |
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- module_name_preceding_first_block: None |
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- batch_size: 1 |
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- pad_token_id: None |
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- use_exllama: False |
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- max_input_length: None |
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- exllama_config: {'version': <ExllamaVersion.ONE: 1>} |
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- cache_block_outputs: True |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- training_steps: 250 |
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- mixed_precision_training: Native AMP |
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### Training results |
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### Framework versions |
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- PEFT 0.7.0 |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
