door_inner_with_SA-bert-base-uncased
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.1513
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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.5492 | 1.0 | 96 | 2.3831 |
| 2.4031 | 2.0 | 192 | 2.2963 |
| 2.3391 | 3.0 | 288 | 2.2000 |
| 2.2951 | 4.0 | 384 | 2.2505 |
| 2.2151 | 5.0 | 480 | 2.1691 |
| 2.2237 | 6.0 | 576 | 2.1855 |
| 2.1984 | 7.0 | 672 | 2.2558 |
| 2.1749 | 8.0 | 768 | 2.2019 |
| 2.1475 | 9.0 | 864 | 2.1310 |
| 2.1446 | 10.0 | 960 | 2.1334 |
| 2.1374 | 11.0 | 1056 | 2.1909 |
| 2.1117 | 12.0 | 1152 | 2.2028 |
Framework versions
- Transformers 4.19.0
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1