distilbert-base-uncased-finetuned-classification
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: 0.7862
- Accuracy: 0.8
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 | 200 | 0.4623 | 0.79 |
| No log | 2.0 | 400 | 0.4932 | 0.7812 |
| 0.3924 | 3.0 | 600 | 0.6621 | 0.7913 |
| 0.3924 | 4.0 | 800 | 0.7862 | 0.8 |
| 0.118 | 5.0 | 1000 | 0.8935 | 0.785 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2