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Tagged_Uni_500v6_NER_Model_3Epochs_AUGMENTED
This model is a fine-tuned version of bert-base-cased on the tagged_uni500v6_wikigold_split dataset. It achieves the following results on the evaluation set:
- Loss: 0.2386
- Precision: 0.6992
- Recall: 0.6987
- F1: 0.6989
- Accuracy: 0.9318
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 | 182 | 0.2452 | 0.5956 | 0.5432 | 0.5682 | 0.9189 |
| No log | 2.0 | 364 | 0.2571 | 0.6832 | 0.6354 | 0.6584 | 0.9204 |
| 0.1093 | 3.0 | 546 | 0.2386 | 0.6992 | 0.6987 | 0.6989 | 0.9318 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.4.0
- Tokenizers 0.11.6
