| language: | |
| - en | |
| license: mit | |
| base_model: xlm-roberta-base | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - tmnam20/VieGLUE | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: xlm-roberta-base-rte-10 | |
| results: | |
| - task: | |
| name: Text Classification | |
| type: text-classification | |
| dataset: | |
| name: tmnam20/VieGLUE/RTE | |
| type: tmnam20/VieGLUE | |
| config: rte | |
| split: validation | |
| args: rte | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.6028880866425993 | |
| <!-- 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. --> | |
| # xlm-roberta-base-rte-10 | |
| This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the tmnam20/VieGLUE/RTE dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.6478 | |
| - Accuracy: 0.6029 | |
| ## 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: 16 | |
| - seed: 10 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3.0 | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.35.2 | |
| - Pytorch 2.2.0.dev20231203+cu121 | |
| - Datasets 2.15.0 | |
| - Tokenizers 0.15.0 | |