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bert-base-uncased-finetuned-vr-comfort-description-review-epoch15-20221107_2125
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: 1.0521
- Accuracy: 0.8443
- F1: 0.8449
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.7304 | 1.0 | 157 | 0.5838 | 0.7521 | 0.6457 |
| 0.6062 | 2.0 | 314 | 0.5416 | 0.7593 | 0.7487 |
| 0.4363 | 3.0 | 471 | 0.4852 | 0.8120 | 0.8139 |
| 0.2679 | 4.0 | 628 | 0.5454 | 0.8204 | 0.8102 |
| 0.164 | 5.0 | 785 | 0.6908 | 0.8060 | 0.8162 |
| 0.112 | 6.0 | 942 | 0.7277 | 0.8287 | 0.8304 |
| 0.0759 | 7.0 | 1099 | 0.9089 | 0.8096 | 0.8192 |
| 0.0323 | 8.0 | 1256 | 0.8422 | 0.8551 | 0.8524 |
| 0.0174 | 9.0 | 1413 | 1.0020 | 0.8299 | 0.8357 |
| 0.0138 | 10.0 | 1570 | 0.9637 | 0.8491 | 0.8473 |
| 0.0057 | 11.0 | 1727 | 1.0195 | 0.8503 | 0.8411 |
| 0.0044 | 12.0 | 1884 | 1.0172 | 0.8455 | 0.8462 |
| 0.0035 | 13.0 | 2041 | 1.0056 | 0.8503 | 0.8487 |
| 0.002 | 14.0 | 2198 | 1.0554 | 0.8443 | 0.8451 |
| 0.0014 | 15.0 | 2355 | 1.0521 | 0.8443 | 0.8449 |
Framework versions
- Transformers 4.13.0
- Pytorch 1.11.0
- Datasets 1.16.1
- Tokenizers 0.10.3
