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Tagged_One_250v5_NER_Model_3Epochs_AUGMENTED
This model is a fine-tuned version of bert-base-cased on the tagged_one250v5_wikigold_split dataset. It achieves the following results on the evaluation set:
- Loss: 0.3623
- Precision: 0.5500
- Recall: 0.4923
- F1: 0.5196
- Accuracy: 0.8950
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 | 91 | 0.3950 | 0.2800 | 0.2138 | 0.2424 | 0.8558 |
| No log | 2.0 | 182 | 0.3633 | 0.4938 | 0.4306 | 0.4601 | 0.8887 |
| No log | 3.0 | 273 | 0.3623 | 0.5500 | 0.4923 | 0.5196 | 0.8950 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.4.0
- Tokenizers 0.11.6
