test-ner
This model is a fine-tuned version of Geotrend/bert-base-th-cased on the lst20 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1910
- Precision: 0.8147
- Recall: 0.8409
- F1: 0.8276
- Accuracy: 0.9379
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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1623 | 1.0 | 3957 | 0.1910 | 0.8147 | 0.8409 | 0.8276 | 0.9379 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Base model
Geotrend/bert-base-th-casedDataset used to train Nattametee01/test-ner
Evaluation results
- Precision on lst20validation set self-reported0.815
- Recall on lst20validation set self-reported0.841
- F1 on lst20validation set self-reported0.828
- Accuracy on lst20validation set self-reported0.938