Tagged_Uni_50v5_NER_Model_3Epochs_AUGMENTED
This model is a fine-tuned version of bert-base-cased on the tagged_uni50v5_wikigold_split dataset. It achieves the following results on the evaluation set:
- Loss: 0.6039
- Precision: 0.2311
- Recall: 0.0350
- F1: 0.0607
- Accuracy: 0.7909
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 | 26 | 0.6534 | 0.0 | 0.0 | 0.0 | 0.7773 |
No log | 2.0 | 52 | 0.6056 | 0.1294 | 0.0097 | 0.0181 | 0.7846 |
No log | 3.0 | 78 | 0.6039 | 0.2311 | 0.0350 | 0.0607 | 0.7909 |
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 tagged_uni50v5_wikigold_splitself-reported0.231
- Recall on tagged_uni50v5_wikigold_splitself-reported0.035
- F1 on tagged_uni50v5_wikigold_splitself-reported0.061
- Accuracy on tagged_uni50v5_wikigold_splitself-reported0.791