| license: mit | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - f1 | |
| model-index: | |
| - name: XLMR_HASOC | |
| 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. --> | |
| # XLMR_HASOC | |
| This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.3081 | |
| - Accuracy: 0.6667 | |
| - F1: 0.6845 | |
| ## 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: 1e-05 | |
| - train_batch_size: 2 | |
| - eval_batch_size: 2 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-05 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_steps: 500 | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | |
| | 0.7501 | 1.0 | 2100 | 0.7108 | 0.6756 | 0.7065 | | |
| | 0.8911 | 2.0 | 4200 | 0.8944 | 0.6739 | 0.7022 | | |
| | 0.9043 | 3.0 | 6300 | 1.3081 | 0.6667 | 0.6845 | | |
| ### Framework versions | |
| - Transformers 4.27.4 | |
| - Pytorch 1.13.1+cu116 | |
| - Datasets 2.11.0 | |
| - Tokenizers 0.13.2 | |