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bert-base-cased-sentweet-derogatory
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9154
- Accuracy: 0.8056
- Precision: 0.8051
- Recall: 0.8036
- F1: 0.8042
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: 5e-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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 81 | 0.4357 | 0.8160 | 0.8194 | 0.8197 | 0.8160 |
| No log | 2.0 | 162 | 0.4131 | 0.7986 | 0.7998 | 0.8010 | 0.7985 |
| No log | 3.0 | 243 | 0.5515 | 0.7812 | 0.7838 | 0.7766 | 0.7780 |
| No log | 4.0 | 324 | 0.6149 | 0.75 | 0.7549 | 0.7435 | 0.7446 |
| No log | 5.0 | 405 | 0.7479 | 0.8125 | 0.8130 | 0.8145 | 0.8124 |
| No log | 6.0 | 486 | 0.9154 | 0.8056 | 0.8051 | 0.8036 | 0.8042 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.1+cu117
- Datasets 2.6.1
- Tokenizers 0.11.0
