Article_250v0_NER_Model_3Epochs_UNAUGMENTED
This model is a fine-tuned version of bert-base-cased on the article250v0_wikigold_split dataset. It achieves the following results on the evaluation set:
- Loss: 0.3397
- Precision: 0.316
- Recall: 0.2984
- F1: 0.3070
- Accuracy: 0.8677
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 28 | 0.5344 | 0.1336 | 0.0183 | 0.0323 | 0.7903 |
| No log | 2.0 | 56 | 0.3736 | 0.2753 | 0.2221 | 0.2458 | 0.8528 |
| No log | 3.0 | 84 | 0.3397 | 0.316 | 0.2984 | 0.3070 | 0.8677 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.4.0
- Tokenizers 0.11.6
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Evaluation results
- Precision on article250v0_wikigold_splitself-reported0.316
- Recall on article250v0_wikigold_splitself-reported0.298
- F1 on article250v0_wikigold_splitself-reported0.307
- Accuracy on article250v0_wikigold_splitself-reported0.868