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bert-base-cased-rte
This model is a fine-tuned version of bert-base-cased on the GLUE RTE dataset. It achieves the following results on the evaluation set:
- Loss: 0.9753
- Accuracy: 0.6534
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 |
|---|---|---|---|---|
| 0.4837 | 3.21 | 500 | 0.9753 | 0.6534 |
| 0.0827 | 6.41 | 1000 | 1.6693 | 0.6715 |
| 0.0253 | 9.62 | 1500 | 1.7777 | 0.6643 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.7.1
- Datasets 1.18.3
- Tokenizers 0.11.6
