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Tagged_Uni_250v3_NER_Model_3Epochs_AUGMENTED
This model is a fine-tuned version of bert-base-cased on the tagged_uni250v3_wikigold_split dataset. It achieves the following results on the evaluation set:
- Loss: 0.3093
- Precision: 0.5831
- Recall: 0.4849
- F1: 0.5295
- Accuracy: 0.8989
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 | 78 | 0.3468 | 0.3486 | 0.2362 | 0.2816 | 0.8670 |
| No log | 2.0 | 156 | 0.3071 | 0.5484 | 0.4516 | 0.4953 | 0.8943 |
| No log | 3.0 | 234 | 0.3093 | 0.5831 | 0.4849 | 0.5295 | 0.8989 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.4.0
- Tokenizers 0.11.6
