bert-large-uncased-finetuned-DA-Zero-shot
This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1318
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: 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: 10.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.1282 | 1.0 | 435 | 1.3862 |
| 1.1307 | 2.0 | 870 | 1.3362 |
| 1.2243 | 3.0 | 1305 | 1.2791 |
| 1.274 | 4.0 | 1740 | 1.2143 |
| 1.2296 | 5.0 | 2175 | 1.1799 |
| 1.1773 | 6.0 | 2610 | 1.1550 |
| 1.1519 | 7.0 | 3045 | 1.1295 |
| 1.1406 | 8.0 | 3480 | 1.1064 |
| 1.114 | 9.0 | 3915 | 1.1303 |
| 1.1058 | 10.0 | 4350 | 1.1214 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2