bert-base-phia-test
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: 0.0910
- F1: 0.9900
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 50 | 1.4259 | 0.5356 |
| No log | 2.0 | 100 | 0.9857 | 0.6872 |
| No log | 3.0 | 150 | 0.6589 | 0.7432 |
| 1.2595 | 4.0 | 200 | 0.4964 | 0.7834 |
| 1.2595 | 5.0 | 250 | 0.3924 | 0.8645 |
| 1.2595 | 6.0 | 300 | 0.2486 | 0.9424 |
| 1.2595 | 7.0 | 350 | 0.1698 | 0.9673 |
| 0.3376 | 8.0 | 400 | 0.1360 | 0.9763 |
| 0.3376 | 9.0 | 450 | 0.1050 | 0.9763 |
| 0.3376 | 10.0 | 500 | 0.0910 | 0.9900 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for reiffd/bert-base-phia-test
Base model
google-bert/bert-base-uncased