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roberta-large-finetuned-disaster
This model is a fine-tuned version of roberta-large on the Disaster Tweets. It achieves the following results on the evaluation set:
- Loss: 0.3668
- Accuracy: 0.8399
- F1: 0.8396
Model description
The model is a fine-tuned version on the disaster dataset on Kaggle. You can enter the following statement to see if the label changes:
Forest fire near La Ronge Sask. Canada
Just happened a terrible car crash
What's up man?
Summer is lovely
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|---|
| 0.446 | 1.0 | 226 | 0.3657 | 0.8583 | 0.8580 |
| 0.3295 | 2.0 | 452 | 0.3668 | 0.8399 | 0.8396 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2
