| base_model: uitnlp/visobert | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - f1 | |
| - precision | |
| - recall | |
| model-index: | |
| - name: facebook-commet-classification-base | |
| 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. --> | |
| # facebook-commet-classification-base | |
| This model is a fine-tuned version of [uitnlp/visobert](https://huggingface.co./uitnlp/visobert) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0642 | |
| - Accuracy: 0.9830 | |
| - F1: 0.9568 | |
| - Precision: 0.9441 | |
| - Recall: 0.9698 | |
| ## 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: 5e-05 | |
| - train_batch_size: 3 | |
| - eval_batch_size: 3 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 1 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | |
| | 0.0616 | 1.0 | 2376 | 0.0642 | 0.9830 | 0.9568 | 0.9441 | 0.9698 | | |
| ### Framework versions | |
| - Transformers 4.38.2 | |
| - Pytorch 2.2.1+cu121 | |
| - Datasets 2.17.0 | |
| - Tokenizers 0.15.2 | |