hate_BERTimbau_v3
This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7782
- Precision: 0.7641
- Recall: 0.7690
- F1: 0.7621
- Accuracy: 0.7690
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.5887 | 1.0 | 284 | 0.5397 | 0.7478 | 0.7319 | 0.7362 | 0.7319 |
0.4617 | 2.0 | 568 | 0.4880 | 0.7842 | 0.7090 | 0.7136 | 0.7090 |
0.3256 | 3.0 | 852 | 0.7394 | 0.7646 | 0.7690 | 0.7603 | 0.7690 |
0.2023 | 4.0 | 1136 | 0.8880 | 0.7808 | 0.7831 | 0.7816 | 0.7831 |
0.1305 | 5.0 | 1420 | 1.0510 | 0.7747 | 0.7619 | 0.7654 | 0.7619 |
0.0916 | 6.0 | 1704 | 1.4921 | 0.7452 | 0.7496 | 0.7464 | 0.7496 |
0.0494 | 7.0 | 1988 | 1.7782 | 0.7641 | 0.7690 | 0.7621 | 0.7690 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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neuralmind/bert-base-portuguese-cased
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