bert-base-portuguese-cased_harem-sm-first-ner
This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the harem dataset. It achieves the following results on the evaluation set:
- Loss: 0.1952
- Precision: 0.7456
- Recall: 0.8053
- F1: 0.7743
- Accuracy: 0.9649
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1049 | 1.0 | 2517 | 0.1955 | 0.6601 | 0.7710 | 0.7113 | 0.9499 |
| 0.0622 | 2.0 | 5034 | 0.2097 | 0.7314 | 0.7901 | 0.7596 | 0.9554 |
| 0.0318 | 3.0 | 7551 | 0.1952 | 0.7456 | 0.8053 | 0.7743 | 0.9649 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.2+cu102
- Datasets 2.2.2
- Tokenizers 0.12.1
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Dataset used to train jordyvl/bert-base-portuguese-cased_harem-selective-sm-first-ner
Evaluation results
- Precision on haremself-reported0.746
- Recall on haremself-reported0.805
- F1 on haremself-reported0.774
- Accuracy on haremself-reported0.965