distilbert-base-uncased_output
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: 0.9385
- Accuracy: 0.3333
- F1: 0.5
- Precision: 0.3333
- Recall: 1.0
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.669 | 1.0 | 12 | 0.6793 | 0.5 | 0.6667 | 0.5 | 1.0 |
| 0.5872 | 2.0 | 24 | 0.6608 | 0.5 | 0.6667 | 0.5 | 1.0 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu102
- Datasets 2.5.1
- Tokenizers 0.13.1