| --- |
| license: apache-2.0 |
| library_name: peft |
| tags: |
| - generated_from_trainer |
| base_model: mistralai/Mistral-7B-v0.1 |
| model-index: |
| - name: org_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_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: 0.9527 |
| - F1 Micro: 0.8011 |
| - F1 Macro: 0.7779 |
| - F1 Weighted: 0.8108 |
| |
| ## 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 | |
| |:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:| |
| | 1.5515 | 0.0064 | 25 | 1.3111 | 0.7801 | 0.7504 | 0.7890 | |
| | 1.2983 | 0.0127 | 50 | 1.2188 | 0.7748 | 0.7572 | 0.7891 | |
| | 1.2193 | 0.0191 | 75 | 1.1271 | 0.7855 | 0.7583 | 0.7937 | |
| | 1.1269 | 0.0255 | 100 | 1.0890 | 0.7952 | 0.7639 | 0.8015 | |
| | 1.0734 | 0.0318 | 125 | 1.0594 | 0.7949 | 0.7635 | 0.8008 | |
| | 1.0384 | 0.0382 | 150 | 1.0389 | 0.7857 | 0.7614 | 0.7937 | |
| | 1.0168 | 0.0446 | 175 | 1.0126 | 0.8045 | 0.7794 | 0.8133 | |
| | 1.0043 | 0.0510 | 200 | 0.9998 | 0.8034 | 0.7786 | 0.8123 | |
| | 1.0406 | 0.0573 | 225 | 0.9874 | 0.8074 | 0.7803 | 0.8153 | |
| | 1.0488 | 0.0637 | 250 | 0.9838 | 0.7922 | 0.7664 | 0.8000 | |
| | 0.9894 | 0.0701 | 275 | 0.9673 | 0.8034 | 0.7780 | 0.8122 | |
| | 0.9969 | 0.0764 | 300 | 0.9629 | 0.7992 | 0.7720 | 0.8069 | |
| | 1.0047 | 0.0828 | 325 | 0.9655 | 0.8000 | 0.7689 | 0.8058 | |
| | 0.9812 | 0.0892 | 350 | 0.9623 | 0.8049 | 0.7839 | 0.8159 | |
| | 0.9681 | 0.0955 | 375 | 0.9551 | 0.8016 | 0.7794 | 0.8118 | |
| | 1.0594 | 0.1019 | 400 | 0.9527 | 0.8011 | 0.7779 | 0.8108 | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.10.0 |
| - Transformers 4.40.2 |
| - Pytorch 2.3.0+cu118 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
