| --- |
| license: apache-2.0 |
| base_model: sentence-transformers/LaBSE |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: binary_persian_sentiment_analysis |
| 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. --> |
|
|
| # binary_persian_sentiment_analysis |
| |
| This model is a fine-tuned version of [sentence-transformers/LaBSE](https://huggingface.co/sentence-transformers/LaBSE) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5060 |
| - Accuracy: 0.8805 |
| - F1 Score: 0.8805 |
| |
| ## 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: 2e-05 |
| - train_batch_size: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | |
| |:-------------:|:-----:|:------:|:---------------:|:--------:|:--------:| |
| | 0.5045 | 1.0 | 8359 | 0.5295 | 0.8816 | 0.8814 | |
| | 0.4211 | 2.0 | 16718 | 0.6029 | 0.8837 | 0.8837 | |
| | 0.3501 | 3.0 | 25077 | 0.5060 | 0.8805 | 0.8805 | |
| | 0.2541 | 4.0 | 33436 | 0.7740 | 0.8762 | 0.8762 | |
| | 0.2065 | 5.0 | 41795 | 0.8071 | 0.8746 | 0.8745 | |
| | 0.1915 | 6.0 | 50154 | 0.8341 | 0.8805 | 0.8805 | |
| | 0.137 | 7.0 | 58513 | 0.9235 | 0.8644 | 0.8644 | |
| | 0.0605 | 8.0 | 66872 | 0.9695 | 0.8584 | 0.8584 | |
| | 0.0405 | 9.0 | 75231 | 1.0090 | 0.8751 | 0.8751 | |
| | 0.0712 | 10.0 | 83590 | 1.0134 | 0.8767 | 0.8767 | |
| | 0.0295 | 11.0 | 91949 | 1.0266 | 0.8708 | 0.8709 | |
| | 0.0704 | 12.0 | 100308 | 0.9940 | 0.8767 | 0.8767 | |
| | 0.0233 | 13.0 | 108667 | 1.0747 | 0.8762 | 0.8762 | |
| | 0.0153 | 14.0 | 117026 | 1.0747 | 0.8741 | 0.8741 | |
| | 0.0245 | 15.0 | 125385 | 1.0027 | 0.8837 | 0.8837 | |
| | 0.0618 | 16.0 | 133744 | 0.9939 | 0.8778 | 0.8778 | |
| | 0.0087 | 17.0 | 142103 | 1.0448 | 0.8854 | 0.8853 | |
| | 0.0174 | 18.0 | 150462 | 1.0339 | 0.8837 | 0.8838 | |
| | 0.0185 | 19.0 | 158821 | 1.1171 | 0.8778 | 0.8778 | |
| | 0.0075 | 20.0 | 167180 | 1.1022 | 0.8827 | 0.8827 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.0 |
| |
