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Tagged_One_250v1_NER_Model_3Epochs_AUGMENTED
This model is a fine-tuned version of bert-base-cased on the tagged_one250v1_wikigold_split dataset. It achieves the following results on the evaluation set:
- Loss: 0.3321
- Precision: 0.5896
- Recall: 0.5099
- F1: 0.5469
- Accuracy: 0.8999
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 | 89 | 0.3518 | 0.3537 | 0.2945 | 0.3214 | 0.8761 |
| No log | 2.0 | 178 | 0.3115 | 0.5583 | 0.4867 | 0.5201 | 0.8974 |
| No log | 3.0 | 267 | 0.3321 | 0.5896 | 0.5099 | 0.5469 | 0.8999 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.4.0
- Tokenizers 0.11.6
