metadata
license: mit
base_model: dbmdz/bert-base-german-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: bert-base-german-uncased
results: []
bert-base-german-uncased
This model is a fine-tuned version of dbmdz/bert-base-german-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5523
- F1: 0.4333
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-07
- 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: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.6943 | 1.0 | 189 | 0.6839 | 0.08 |
| 0.6718 | 2.0 | 378 | 0.6603 | 0.0339 |
| 0.66 | 3.0 | 567 | 0.6508 | 0.0476 |
| 0.6568 | 4.0 | 756 | 0.6457 | 0.05 |
| 0.6638 | 5.0 | 945 | 0.6439 | 0.0513 |
| 0.6552 | 6.0 | 1134 | 0.6387 | 0.0556 |
| 0.6709 | 7.0 | 1323 | 0.6386 | 0.0556 |
| 0.6541 | 8.0 | 1512 | 0.6369 | 0.0556 |
| 0.6644 | 9.0 | 1701 | 0.6434 | 0.0 |
| 0.6601 | 10.0 | 1890 | 0.6432 | 0.0 |
| 0.6558 | 11.0 | 2079 | 0.6421 | 0.0 |
| 0.6548 | 12.0 | 2268 | 0.6398 | 0.0 |
| 0.6593 | 13.0 | 2457 | 0.6401 | 0.0 |
| 0.6502 | 14.0 | 2646 | 0.6366 | 0.0 |
| 0.6457 | 15.0 | 2835 | 0.6292 | 0.0541 |
| 0.6478 | 16.0 | 3024 | 0.6267 | 0.0541 |
| 0.6378 | 17.0 | 3213 | 0.6311 | 0.0 |
| 0.6325 | 18.0 | 3402 | 0.6279 | 0.0 |
| 0.6467 | 19.0 | 3591 | 0.6253 | 0.0 |
| 0.6338 | 20.0 | 3780 | 0.6227 | 0.0 |
| 0.6281 | 21.0 | 3969 | 0.6194 | 0.0 |
| 0.6205 | 22.0 | 4158 | 0.6155 | 0.0 |
| 0.6288 | 23.0 | 4347 | 0.6113 | 0.0 |
| 0.6178 | 24.0 | 4536 | 0.6081 | 0.0976 |
| 0.6221 | 25.0 | 4725 | 0.6049 | 0.1778 |
| 0.612 | 26.0 | 4914 | 0.6011 | 0.25 |
| 0.6052 | 27.0 | 5103 | 0.5971 | 0.25 |
| 0.5997 | 28.0 | 5292 | 0.5925 | 0.2553 |
| 0.603 | 29.0 | 5481 | 0.5895 | 0.3265 |
| 0.5973 | 30.0 | 5670 | 0.5856 | 0.3200 |
| 0.594 | 31.0 | 5859 | 0.5821 | 0.3200 |
| 0.5825 | 32.0 | 6048 | 0.5786 | 0.3529 |
| 0.5787 | 33.0 | 6237 | 0.5753 | 0.3929 |
| 0.5848 | 34.0 | 6426 | 0.5724 | 0.3929 |
| 0.5703 | 35.0 | 6615 | 0.5698 | 0.4000 |
| 0.584 | 36.0 | 6804 | 0.5673 | 0.3929 |
| 0.5668 | 37.0 | 6993 | 0.5648 | 0.3860 |
| 0.5624 | 38.0 | 7182 | 0.5629 | 0.3860 |
| 0.5793 | 39.0 | 7371 | 0.5611 | 0.4138 |
| 0.5555 | 40.0 | 7560 | 0.5593 | 0.3860 |
| 0.5664 | 41.0 | 7749 | 0.5579 | 0.4407 |
| 0.553 | 42.0 | 7938 | 0.5566 | 0.4483 |
| 0.5597 | 43.0 | 8127 | 0.5555 | 0.4483 |
| 0.5555 | 44.0 | 8316 | 0.5546 | 0.4407 |
| 0.5589 | 45.0 | 8505 | 0.5538 | 0.4333 |
| 0.5578 | 46.0 | 8694 | 0.5531 | 0.4333 |
| 0.5499 | 47.0 | 8883 | 0.5528 | 0.4333 |
| 0.5434 | 48.0 | 9072 | 0.5524 | 0.4333 |
| 0.5607 | 49.0 | 9261 | 0.5523 | 0.4333 |
| 0.5478 | 50.0 | 9450 | 0.5523 | 0.4333 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.12.0
- Tokenizers 0.13.3