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distilbert-base-uncased_finetuned_disaster_tweets
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: 0.4007
- Accuracy: 0.8399
- F1: 0.8384
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4594 | 1.0 | 191 | 0.4059 | 0.8163 | 0.8164 |
| 0.3399 | 2.0 | 382 | 0.3905 | 0.8346 | 0.8333 |
| 0.2859 | 3.0 | 573 | 0.4007 | 0.8399 | 0.8384 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
