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--- |
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license: llama2 |
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base_model: bofenghuang/vigogne-2-70b-chat |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: PointCon-vigogne-2-70b-chat-3 |
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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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# PointCon-vigogne-2-70b-chat-3 |
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This model is a fine-tuned version of [bofenghuang/vigogne-2-70b-chat](https://huggingface.co/bofenghuang/vigogne-2-70b-chat) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5719 |
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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: 5e-05 |
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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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- num_epochs: 1 |
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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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| 1.8556 | 0.05 | 30 | 1.7646 | |
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| 1.6805 | 0.1 | 60 | 1.6982 | |
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| 1.646 | 0.15 | 90 | 1.6679 | |
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| 1.5978 | 0.19 | 120 | 1.6567 | |
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| 1.6003 | 0.24 | 150 | 1.6437 | |
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| 1.5975 | 0.29 | 180 | 1.6339 | |
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| 1.5917 | 0.34 | 210 | 1.6264 | |
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| 1.5579 | 0.39 | 240 | 1.6111 | |
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| 1.5888 | 0.44 | 270 | 1.6022 | |
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| 1.5763 | 0.49 | 300 | 1.5966 | |
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| 1.5102 | 0.54 | 330 | 1.5938 | |
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| 1.5611 | 0.58 | 360 | 1.5877 | |
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| 1.6063 | 0.63 | 390 | 1.5869 | |
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| 1.5641 | 0.68 | 420 | 1.5870 | |
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| 1.5615 | 0.73 | 450 | 1.5808 | |
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| 1.4644 | 0.78 | 480 | 1.5761 | |
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| 1.4924 | 0.83 | 510 | 1.5750 | |
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| 1.5644 | 0.88 | 540 | 1.5735 | |
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| 1.5498 | 0.93 | 570 | 1.5726 | |
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| 1.5179 | 0.97 | 600 | 1.5719 | |
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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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