distilbert-base-uncased-analysis
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: 0.5389
- Accuracy: 0.8914
- F1: 0.8916
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 | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 122 | 0.4851 | 0.8852 | 0.8839 |
| No log | 2.0 | 244 | 0.4917 | 0.8975 | 0.8970 |
| No log | 3.0 | 366 | 0.5336 | 0.8934 | 0.8935 |
| No log | 4.0 | 488 | 0.5214 | 0.8893 | 0.8889 |
| No log | 5.0 | 610 | 0.5389 | 0.8914 | 0.8916 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3