roberta-base-wnli
This model is a fine-tuned version of roberta-base on the GLUE WNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6849
- Accuracy: 0.5634
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 |
|---|---|---|---|---|
| No log | 1.0 | 40 | 0.6849 | 0.5634 |
| No log | 2.0 | 80 | 0.6912 | 0.5634 |
| No log | 3.0 | 120 | 0.6918 | 0.5634 |
| No log | 4.0 | 160 | 0.6964 | 0.4366 |
| No log | 5.0 | 200 | 0.6928 | 0.5634 |
| No log | 6.0 | 240 | 0.7005 | 0.4366 |
| No log | 7.0 | 280 | 0.6964 | 0.3099 |
| No log | 8.0 | 320 | 0.6986 | 0.3521 |
| No log | 9.0 | 360 | 0.6969 | 0.5493 |
| No log | 10.0 | 400 | 0.6976 | 0.5634 |
Framework versions
- Transformers 4.20.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1