bert_seq_tag
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3935
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.4578
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: 0.002
- 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 | 3 | 2.1913 | 0.0 | 0.0 | 0.0 | 0.4578 |
| No log | 2.0 | 6 | 1.5449 | 0.0 | 0.0 | 0.0 | 0.4578 |
| No log | 3.0 | 9 | 1.3935 | 0.0 | 0.0 | 0.0 | 0.4578 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2