results
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8697
- Accuracy: 0.8817
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9803 | 1.0 | 254 | 1.0897 | 0.8836 |
| 0.9664 | 2.0 | 508 | 0.9088 | 0.8540 |
| 0.9575 | 3.0 | 762 | 0.7617 | 0.8363 |
| 0.8724 | 4.0 | 1016 | 0.9282 | 0.8738 |
| 0.9143 | 5.0 | 1270 | 0.8697 | 0.8817 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
distilbert/distilbert-base-uncased