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bert-finetuned-ner-10percent
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5010
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.4556
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: 2022
- 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 | 8 | 1.7713 | 0.0 | 0.0 | 0.0 | 0.4508 |
| No log | 2.0 | 16 | 1.5699 | 0.0 | 0.0 | 0.0 | 0.4517 |
| No log | 3.0 | 24 | 1.5010 | 0.0 | 0.0 | 0.0 | 0.4556 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2
