bert-base-multilingual-cased-finetuned-lener_br
This model is a fine-tuned version of bert-base-multilingual-cased on the Luciano/lener_br_text_to_lm dataset. It achieves the following results on the evaluation set:
- Loss: 0.8132 (To update)
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters (To update)
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results (To update)
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.3167 | 1.0 | 2079 | 1.1163 |
1.1683 | 2.0 | 4158 | 1.0594 |
1.0648 | 3.0 | 6237 | 1.0501 |
1.0228 | 4.0 | 8316 | 0.9693 |
0.9662 | 5.0 | 10395 | 0.9847 |
0.9422 | 6.0 | 12474 | 0.9556 |
0.8696 | 7.0 | 14553 | 0.8978 |
0.7856 | 8.0 | 16632 | nan |
0.7849 | 9.0 | 18711 | 0.9192 |
0.7559 | 10.0 | 20790 | 0.8536 |
0.7564 | 11.0 | 22869 | 0.9230 |
0.7641 | 12.0 | 24948 | 0.8852 |
0.7007 | 13.0 | 27027 | 0.8616 |
0.7139 | 14.0 | 29106 | 0.8419 |
0.6543 | 15.0 | 31185 | 0.8460 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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