| --- |
| library_name: transformers |
| license: mit |
| base_model: roberta-large |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: Modesty_binary |
| 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. --> |
|
|
| # Modesty_binary |
| |
| This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6643 |
| - Accuracy: 0.6782 |
| - Precision: 0.6621 |
| - Recall: 0.7228 |
| - F1: 0.6911 |
| - Auc: 0.6783 |
| |
| ## 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: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auc | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:| |
| | No log | 1.0 | 134 | 0.6134 | 0.6558 | 0.6998 | 0.5412 | 0.6103 | 0.6554 | |
| | No log | 2.0 | 268 | 0.6132 | 0.6791 | 0.7149 | 0.5918 | 0.6475 | 0.6788 | |
| | No log | 3.0 | 402 | 0.6643 | 0.6782 | 0.6621 | 0.7228 | 0.6911 | 0.6783 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.44.1 |
| - Pytorch 1.11.0 |
| - Datasets 2.12.0 |
| - Tokenizers 0.19.1 |
| |
