| license: mit | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| base_model: roberta-large | |
| model-index: | |
| - name: dcai2023-roberta | |
| 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. --> | |
| # dcai2023-roberta | |
| This model is a fine-tuned version of [roberta-large](https://huggingface.co./roberta-large) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.7027 | |
| - Accuracy: 0.7383 | |
| ## 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: 16 | |
| - eval_batch_size: 16 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 2 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| | 0.9281 | 1.0 | 530 | 0.7301 | 0.7136 | | |
| | 0.6474 | 2.0 | 1060 | 0.7027 | 0.7383 | | |
| ### Framework versions | |
| - Transformers 4.26.1 | |
| - Pytorch 1.13.0.post200 | |
| - Datasets 2.9.0 | |
| - Tokenizers 0.13.2 | |