germanic_peoplecentric_eng
This model is a fine-tuned version of google-bert/bert-large-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5708
- Accuracy: 0.7303
- F1: 0.7722
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 76 | 0.6456 | 0.6020 | 0.6533 |
| 0.65 | 2.0 | 152 | 0.6183 | 0.6678 | 0.6752 |
| 0.4963 | 3.0 | 228 | 0.5708 | 0.7303 | 0.7722 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
google-bert/bert-large-cased