NCbC
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: 0.1397
- Accuracy: 0.9775
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: 5e-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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 112 | 0.1497 | 0.9640 |
| No log | 2.0 | 224 | 0.1276 | 0.9730 |
| No log | 3.0 | 336 | 0.0850 | 0.9820 |
| No log | 4.0 | 448 | 0.1359 | 0.9753 |
| 0.1019 | 5.0 | 560 | 0.1388 | 0.9775 |
| 0.1019 | 6.0 | 672 | 0.1397 | 0.9775 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Base model
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