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--- |
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license: llama2 |
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base_model: TheBloke/vigogne-2-70B-chat-GPTQ |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Vigogne70b-fans |
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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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# Vigogne70b-fans |
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This model is a fine-tuned version of [TheBloke/vigogne-2-70B-chat-GPTQ](https://huggingface.co/TheBloke/vigogne-2-70B-chat-GPTQ) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9593 |
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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: 0.0004 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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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: linear |
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- lr_scheduler_warmup_steps: 2 |
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- training_steps: 200 |
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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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| 1.9503 | 0.02 | 10 | 1.6354 | |
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| 1.2959 | 0.04 | 20 | 1.2117 | |
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| 1.2316 | 0.07 | 30 | 1.1256 | |
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| 1.1742 | 0.09 | 40 | 1.0960 | |
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| 1.1643 | 0.11 | 50 | 1.0677 | |
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| 1.0667 | 0.13 | 60 | 1.0449 | |
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| 1.0232 | 0.15 | 70 | 1.0391 | |
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| 0.9864 | 0.17 | 80 | 1.0272 | |
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| 1.0588 | 0.2 | 90 | 1.0206 | |
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| 0.906 | 0.22 | 100 | 1.0020 | |
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| 1.098 | 0.24 | 110 | 0.9979 | |
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| 0.9973 | 0.26 | 120 | 0.9883 | |
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| 0.9999 | 0.28 | 130 | 1.0002 | |
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| 1.121 | 0.31 | 140 | 0.9752 | |
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| 0.9726 | 0.33 | 150 | 0.9722 | |
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| 1.015 | 0.35 | 160 | 0.9680 | |
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| 0.8247 | 0.37 | 170 | 0.9664 | |
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| 0.823 | 0.39 | 180 | 0.9613 | |
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| 0.8921 | 0.41 | 190 | 0.9607 | |
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| 1.0024 | 0.44 | 200 | 0.9593 | |
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### Framework versions |
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- Transformers 4.35.2 |
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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 |
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