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--- |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-v0.1 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: mistral-customerSupport-finetune |
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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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# mistral-customerSupport-finetune |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6550 |
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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: 2.5e-05 |
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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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- 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: 1 |
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- training_steps: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.8511 | 0.03 | 25 | 1.0647 | |
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| 0.6109 | 0.06 | 50 | 1.0602 | |
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| 0.6824 | 0.09 | 75 | 1.0368 | |
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| 0.876 | 0.12 | 100 | 0.9630 | |
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| 0.9261 | 0.15 | 125 | 0.9391 | |
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| 0.8642 | 0.18 | 150 | 0.9180 | |
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| 0.8901 | 0.21 | 175 | 0.9037 | |
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| 0.9167 | 0.24 | 200 | 0.8685 | |
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| 0.8831 | 0.27 | 225 | 0.8505 | |
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| 0.7935 | 0.3 | 250 | 0.8341 | |
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| 0.8635 | 0.33 | 275 | 0.8203 | |
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| 0.7317 | 0.36 | 300 | 0.8052 | |
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| 0.7195 | 0.39 | 325 | 0.7996 | |
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| 0.8332 | 0.42 | 350 | 0.7847 | |
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| 0.799 | 0.44 | 375 | 0.7733 | |
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| 0.6985 | 0.47 | 400 | 0.7677 | |
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| 0.7192 | 0.5 | 425 | 0.7594 | |
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| 0.7391 | 0.53 | 450 | 0.7459 | |
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| 0.6792 | 0.56 | 475 | 0.7312 | |
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| 0.8249 | 0.59 | 500 | 0.7299 | |
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| 0.6745 | 0.62 | 525 | 0.7193 | |
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| 0.6625 | 0.65 | 550 | 0.7233 | |
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| 0.5941 | 0.68 | 575 | 0.7132 | |
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| 0.704 | 0.71 | 600 | 0.7072 | |
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| 0.636 | 0.74 | 625 | 0.7002 | |
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| 0.6401 | 0.77 | 650 | 0.6958 | |
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| 0.773 | 0.8 | 675 | 0.6876 | |
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| 0.5974 | 0.83 | 700 | 0.6840 | |
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| 0.6062 | 0.86 | 725 | 0.6729 | |
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| 0.5464 | 0.89 | 750 | 0.6664 | |
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| 0.6384 | 0.92 | 775 | 0.6633 | |
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| 0.6292 | 0.95 | 800 | 0.6594 | |
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| 0.6629 | 0.98 | 825 | 0.6564 | |
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| 0.6414 | 1.01 | 850 | 0.6524 | |
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| 0.4689 | 1.04 | 875 | 0.6549 | |
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| 0.3982 | 1.07 | 900 | 0.6627 | |
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| 0.4089 | 1.1 | 925 | 0.6583 | |
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| 0.4483 | 1.13 | 950 | 0.6566 | |
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| 0.429 | 1.16 | 975 | 0.6555 | |
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| 0.4088 | 1.19 | 1000 | 0.6550 | |
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### Framework versions |
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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 |
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