| --- |
| license: apache-2.0 |
| library_name: peft |
| tags: |
| - generated_from_trainer |
| base_model: mistralai/Mistral-7B-v0.1 |
| model-index: |
| - name: org_modelorg_model |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # org_modelorg_model |
|
|
| This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.0305 |
| - F1 Micro: 0.7988 |
| - F1 Macro: 0.7745 |
| - F1 Weighted: 0.8091 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 0.0001 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - training_steps: 400 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | F1 Weighted | |
| |:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:| |
| | 1.7847 | 0.0064 | 25 | 1.4983 | 0.7827 | 0.7547 | 0.7929 | |
| | 1.3333 | 0.0127 | 50 | 1.2986 | 0.7926 | 0.7660 | 0.8031 | |
| | 1.2721 | 0.0191 | 75 | 1.2255 | 0.7755 | 0.7520 | 0.7862 | |
| | 1.127 | 0.0255 | 100 | 1.1722 | 0.7945 | 0.7694 | 0.8053 | |
| | 1.1108 | 0.0318 | 125 | 1.1561 | 0.7922 | 0.7556 | 0.7971 | |
| | 1.0969 | 0.0382 | 150 | 1.1181 | 0.7875 | 0.7581 | 0.7955 | |
| | 1.0714 | 0.0446 | 175 | 1.1001 | 0.7884 | 0.7658 | 0.7993 | |
| | 1.0219 | 0.0510 | 200 | 1.0758 | 0.8000 | 0.7727 | 0.8091 | |
| | 1.0979 | 0.0573 | 225 | 1.0671 | 0.7973 | 0.7656 | 0.8040 | |
| | 1.0846 | 0.0637 | 250 | 1.0632 | 0.7866 | 0.7582 | 0.7944 | |
| | 0.9977 | 0.0701 | 275 | 1.0590 | 0.7934 | 0.7600 | 0.7991 | |
| | 1.1262 | 0.0764 | 300 | 1.0404 | 0.7984 | 0.7699 | 0.8066 | |
| | 1.0066 | 0.0828 | 325 | 1.0396 | 0.7981 | 0.7681 | 0.8053 | |
| | 1.0534 | 0.0892 | 350 | 1.0360 | 0.8005 | 0.7768 | 0.8113 | |
| | 1.0302 | 0.0955 | 375 | 1.0320 | 0.7993 | 0.7754 | 0.8099 | |
| | 1.0965 | 0.1019 | 400 | 1.0305 | 0.7988 | 0.7745 | 0.8091 | |
|
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|
|
| ### Framework versions |
|
|
| - PEFT 0.10.0 |
| - Transformers 4.40.2 |
| - Pytorch 2.3.0+cu118 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
