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covid-augment-tweet-bert-large-e4
This model is a fine-tuned version of digitalepidemiologylab/covid-twitter-bert-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3723
- Accuracy: 0.9587
- F1: 0.8889
- Precision: 0.8920
- Recall: 0.8858
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.1307 | 1.0 | 4089 | 0.3055 | 0.9523 | 0.8771 | 0.8435 | 0.9135 |
| 0.0367 | 2.0 | 8178 | 0.3270 | 0.9568 | 0.8885 | 0.8558 | 0.9239 |
| 0.0133 | 3.0 | 12267 | 0.3316 | 0.9600 | 0.8949 | 0.8771 | 0.9135 |
| 0.0007 | 4.0 | 16356 | 0.3723 | 0.9587 | 0.8889 | 0.8920 | 0.8858 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
