parsbert-finetuned-pos
This model is a fine-tuned version of HooshvareLab/bert-base-parsbert-uncased on the udpos28 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1385
- Precision: 0.9448
- Recall: 0.9486
- F1: 0.9467
- Accuracy: 0.9599
Model description
More information needed
Intended uses & limitations
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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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.122 | 1.0 | 3103 | 0.1215 | 0.9363 | 0.9424 | 0.9394 | 0.9561 |
0.0735 | 2.0 | 6206 | 0.1297 | 0.9413 | 0.9474 | 0.9443 | 0.9582 |
0.0373 | 3.0 | 9309 | 0.1385 | 0.9448 | 0.9486 | 0.9467 | 0.9599 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0
- Datasets 2.0.0
- Tokenizers 0.11.6
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Evaluation results
- Precision on udpos28self-reported0.945
- Recall on udpos28self-reported0.949
- F1 on udpos28self-reported0.947
- Accuracy on udpos28self-reported0.960