Bert-fine-tuned-WiC
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6958
- Accuracy: 0.6881
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6164 | 1.0 | 679 | 0.6806 | 0.6865 |
| 0.4214 | 2.0 | 1358 | 1.0573 | 0.6646 |
| 0.2186 | 3.0 | 2037 | 1.3339 | 0.6897 |
| 0.1485 | 4.0 | 2716 | 1.5803 | 0.6881 |
| 0.115 | 5.0 | 3395 | 1.6958 | 0.6881 |
Framework versions
- Transformers 4.39.3
- Pytorch 1.13.0
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for rycecorn/Bert-fine-tuned-WiC
Base model
google-bert/bert-base-uncased