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bert-base-uncased-finetuned-semeval2020-task4a
This model is a fine-tuned version of bert-base-uncased on the ComVE dataset which was part of SemEval 2020 Task 4. It achieves the following results on the test set:
- Loss: 0.2782
- Accuracy: 0.9040
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 344 | 0.2700 | 0.8940 |
| 0.349 | 2.0 | 688 | 0.2782 | 0.9040 |
Framework versions
- Transformers 4.12.3
- Pytorch 1.9.1
- Datasets 1.12.1
- Tokenizers 0.10.3
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