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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-v0.1 |
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datasets: |
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- generator |
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model-index: |
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- name: lc-7b-sft-lora |
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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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# lc-7b-sft-lora |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4782 |
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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: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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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- num_epochs: 20 |
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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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| 1.6469 | 1.0 | 16 | 1.6182 | |
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| 1.5733 | 2.0 | 32 | 1.5646 | |
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| 1.5088 | 3.0 | 48 | 1.5251 | |
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| 1.4873 | 4.0 | 64 | 1.4960 | |
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| 1.4409 | 5.0 | 80 | 1.4758 | |
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| 1.4061 | 6.0 | 96 | 1.4655 | |
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| 1.4014 | 7.0 | 112 | 1.4588 | |
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| 1.3723 | 8.0 | 128 | 1.4573 | |
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| 1.346 | 9.0 | 144 | 1.4604 | |
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| 1.306 | 10.0 | 160 | 1.4605 | |
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| 1.307 | 11.0 | 176 | 1.4639 | |
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| 1.3115 | 12.0 | 192 | 1.4663 | |
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| 1.3093 | 13.0 | 208 | 1.4683 | |
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| 1.2644 | 14.0 | 224 | 1.4705 | |
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| 1.2641 | 15.0 | 240 | 1.4748 | |
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| 1.2578 | 16.0 | 256 | 1.4754 | |
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| 1.2538 | 17.0 | 272 | 1.4771 | |
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| 1.2611 | 18.0 | 288 | 1.4779 | |
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| 1.2609 | 19.0 | 304 | 1.4783 | |
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| 1.2805 | 20.0 | 320 | 1.4782 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
