Religion-Classification
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0585
- Accuracy: 0.9926
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 |
|---|---|---|---|---|
| 0.0722 | 1.0 | 6947 | 0.0671 | 0.9855 |
| 0.0368 | 2.0 | 13894 | 0.0470 | 0.9907 |
| 0.0205 | 3.0 | 20841 | 0.0431 | 0.9918 |
| 0.0109 | 4.0 | 27788 | 0.0576 | 0.9920 |
| 0.0013 | 5.0 | 34735 | 0.0585 | 0.9926 |
Framework versions
- Transformers 4.14.1
- Pytorch 1.12.0
- Datasets 2.9.0
- Tokenizers 0.10.3
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