distilbert-base-uncased-tweets-disaster
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: 0.6060
- Accuracy: 0.8189
- F1: 0.8180
- Precision: 0.7945
- Recall: 0.7484
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: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|---|---|---|---|
| 0.1515 | 1.0 | 113 | 0.5913 | 0.8215 | 0.8197 | 0.8129 | 0.7290 |
| 0.1317 | 2.0 | 226 | 0.6060 | 0.8189 | 0.8180 | 0.7945 | 0.7484 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3