textclassifier
This model is a fine-tuned version of distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.6439
- Accuracy: 0.0
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 4.4693 | 1.0 | 33 | 4.4433 | 0.0 |
| 4.4849 | 2.0 | 66 | 4.5026 | 0.0 |
| 4.4433 | 3.0 | 99 | 4.5717 | 0.0 |
| 4.4234 | 4.0 | 132 | 4.5887 | 0.0 |
| 4.4015 | 5.0 | 165 | 4.6163 | 0.0 |
| 4.3956 | 6.0 | 198 | 4.6046 | 0.0 |
| 4.3878 | 7.0 | 231 | 4.6354 | 0.0 |
| 4.3759 | 8.0 | 264 | 4.6372 | 0.0 |
| 4.3787 | 9.0 | 297 | 4.6405 | 0.0 |
| 4.3678 | 10.0 | 330 | 4.6439 | 0.0 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Model tree for ruru2701/textclassifier
Base model
distilbert/distilbert-base-cased