paraphrase-bert-portuguese
This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the glue-ptpt dataset. It achieves the following results on the evaluation set:
- Loss: 1.2267
- Accuracy: 0.8676
- F1: 0.9029
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: 8
- eval_batch_size: 8
- 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 | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 459 | 0.7241 | 0.8603 | 0.9012 |
0.0658 | 2.0 | 918 | 0.7902 | 0.8725 | 0.9071 |
0.1499 | 3.0 | 1377 | 0.7895 | 0.8676 | 0.9022 |
0.0654 | 4.0 | 1836 | 0.9841 | 0.8676 | 0.9036 |
0.018 | 5.0 | 2295 | 1.0520 | 0.8627 | 0.8989 |
0.0144 | 6.0 | 2754 | 1.1002 | 0.8725 | 0.9081 |
0.007 | 7.0 | 3213 | 1.1303 | 0.8652 | 0.9005 |
0.0056 | 8.0 | 3672 | 1.2298 | 0.8725 | 0.9081 |
0.0019 | 9.0 | 4131 | 1.2353 | 0.8701 | 0.9038 |
0.0001 | 10.0 | 4590 | 1.2267 | 0.8676 | 0.9029 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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Model tree for erickrribeiro/paraphrase-bert-portuguese
Base model
neuralmind/bert-base-portuguese-casedEvaluation results
- Accuracy on glue-ptptvalidation set self-reported0.868
- F1 on glue-ptptvalidation set self-reported0.903