custom-textcat-model
This model is a fine-tuned version of bert-base-multilingual-uncased on the custom dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.3305
- Accuracy: 0.9541
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 209 | 0.3650 | 0.9514 |
| No log | 2.0 | 418 | 0.3371 | 0.9568 |
| 0.0108 | 3.0 | 627 | 0.3305 | 0.9541 |
| 0.0108 | 4.0 | 836 | 0.3465 | 0.9568 |
| 0.0056 | 5.0 | 1045 | 0.3498 | 0.9541 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2