| language: | |
| - en | |
| license: mit | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - glue | |
| metrics: | |
| - accuracy | |
| base_model: roberta-base | |
| model-index: | |
| - name: roberta-base-sst2 | |
| results: | |
| - task: | |
| type: text-classification | |
| name: Text Classification | |
| dataset: | |
| name: GLUE SST2 | |
| type: glue | |
| args: sst2 | |
| metrics: | |
| - type: accuracy | |
| value: 0.9357798165137615 | |
| name: Accuracy | |
| <!-- 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. --> | |
| # roberta-base-sst2 | |
| This model is a fine-tuned version of [roberta-base](https://huggingface.co./roberta-base) on the GLUE SST2 dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.2314 | |
| - Accuracy: 0.9358 | |
| ## 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: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_ratio: 0.06 | |
| - num_epochs: 10.0 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| | |
| | 0.2287 | 1.0 | 4210 | 0.2314 | 0.9358 | | |
| | 0.1959 | 2.0 | 8420 | 0.3027 | 0.9266 | | |
| | 0.1635 | 3.0 | 12630 | 0.3022 | 0.9300 | | |
| | 0.1148 | 4.0 | 16840 | 0.3162 | 0.9289 | | |
| ### Framework versions | |
| - Transformers 4.20.0.dev0 | |
| - Pytorch 1.11.0+cu113 | |
| - Datasets 2.1.0 | |
| - Tokenizers 0.12.1 | |