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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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- trl |
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- sft |
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- generated_from_trainer |
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base_model: mistralai/Mistral-7B-Instruct-v0.2 |
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datasets: |
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- generator |
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model-index: |
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- name: cls_alldata_mistral_v1 |
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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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# cls_alldata_mistral_v1 |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4126 |
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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: 0.0002 |
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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: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 2 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.5676 | 0.1091 | 20 | 0.5817 | |
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| 0.5158 | 0.2183 | 40 | 0.5408 | |
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| 0.5124 | 0.3274 | 60 | 0.5162 | |
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| 0.4791 | 0.4366 | 80 | 0.4999 | |
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| 0.4762 | 0.5457 | 100 | 0.4850 | |
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| 0.4724 | 0.6548 | 120 | 0.4737 | |
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| 0.4423 | 0.7640 | 140 | 0.4611 | |
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| 0.4453 | 0.8731 | 160 | 0.4508 | |
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| 0.4179 | 0.9823 | 180 | 0.4412 | |
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| 0.3243 | 1.0914 | 200 | 0.4479 | |
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| 0.3198 | 1.2005 | 220 | 0.4383 | |
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| 0.3012 | 1.3097 | 240 | 0.4335 | |
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| 0.3135 | 1.4188 | 260 | 0.4315 | |
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| 0.3081 | 1.5280 | 280 | 0.4247 | |
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| 0.3048 | 1.6371 | 300 | 0.4193 | |
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| 0.322 | 1.7462 | 320 | 0.4150 | |
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| 0.3034 | 1.8554 | 340 | 0.4136 | |
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| 0.3188 | 1.9645 | 360 | 0.4126 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
