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---
license: mit
base_model: deepset/gbert-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: gbert-base
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gbert-base
This model is a fine-tuned version of [deepset/gbert-base](https://huggingface.co/deepset/gbert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6361
- F1: 0.0
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 0.6805 | 1.0 | 189 | 0.6439 | 0.0 |
| 0.6838 | 2.0 | 378 | 0.6409 | 0.0 |
| 0.6668 | 3.0 | 567 | 0.6376 | 0.0 |
| 0.6666 | 4.0 | 756 | 0.6388 | 0.0 |
| 0.684 | 5.0 | 945 | 0.6372 | 0.0 |
| 0.673 | 6.0 | 1134 | 0.6419 | 0.0 |
| 0.7006 | 7.0 | 1323 | 0.6381 | 0.0 |
| 0.6819 | 8.0 | 1512 | 0.6404 | 0.0 |
| 0.6937 | 9.0 | 1701 | 0.6387 | 0.0 |
| 0.6809 | 10.0 | 1890 | 0.6375 | 0.0 |
| 0.6753 | 11.0 | 2079 | 0.6386 | 0.0 |
| 0.6688 | 12.0 | 2268 | 0.6449 | 0.0 |
| 0.6898 | 13.0 | 2457 | 0.6407 | 0.0 |
| 0.6682 | 14.0 | 2646 | 0.6458 | 0.0 |
| 0.6923 | 15.0 | 2835 | 0.6498 | 0.0 |
| 0.6961 | 16.0 | 3024 | 0.6482 | 0.0 |
| 0.6934 | 17.0 | 3213 | 0.6432 | 0.0 |
| 0.6853 | 18.0 | 3402 | 0.6457 | 0.0 |
| 0.6747 | 19.0 | 3591 | 0.6489 | 0.0 |
| 0.6939 | 20.0 | 3780 | 0.6465 | 0.0 |
| 0.6838 | 21.0 | 3969 | 0.6425 | 0.0 |
| 0.6725 | 22.0 | 4158 | 0.6401 | 0.0 |
| 0.6736 | 23.0 | 4347 | 0.6435 | 0.0 |
| 0.6705 | 24.0 | 4536 | 0.6425 | 0.0 |
| 0.6838 | 25.0 | 4725 | 0.6408 | 0.0 |
| 0.6742 | 26.0 | 4914 | 0.6417 | 0.0 |
| 0.6658 | 27.0 | 5103 | 0.6405 | 0.0 |
| 0.6672 | 28.0 | 5292 | 0.6445 | 0.0 |
| 0.6845 | 29.0 | 5481 | 0.6403 | 0.0 |
| 0.661 | 30.0 | 5670 | 0.6408 | 0.0 |
| 0.6775 | 31.0 | 5859 | 0.6394 | 0.0 |
| 0.6556 | 32.0 | 6048 | 0.6420 | 0.0 |
| 0.6708 | 33.0 | 6237 | 0.6387 | 0.0 |
| 0.6633 | 34.0 | 6426 | 0.6384 | 0.0 |
| 0.6536 | 35.0 | 6615 | 0.6401 | 0.0 |
| 0.6681 | 36.0 | 6804 | 0.6383 | 0.0 |
| 0.6573 | 37.0 | 6993 | 0.6381 | 0.0 |
| 0.6489 | 38.0 | 7182 | 0.6381 | 0.0 |
| 0.6806 | 39.0 | 7371 | 0.6347 | 0.0 |
| 0.6267 | 40.0 | 7560 | 0.6373 | 0.0 |
| 0.6577 | 41.0 | 7749 | 0.6343 | 0.0 |
| 0.6464 | 42.0 | 7938 | 0.6347 | 0.0 |
| 0.6325 | 43.0 | 8127 | 0.6361 | 0.0 |
| 0.6583 | 44.0 | 8316 | 0.6363 | 0.0 |
| 0.6634 | 45.0 | 8505 | 0.6355 | 0.0 |
| 0.6504 | 46.0 | 8694 | 0.6347 | 0.0 |
| 0.6457 | 47.0 | 8883 | 0.6356 | 0.0 |
| 0.632 | 48.0 | 9072 | 0.6362 | 0.0 |
| 0.651 | 49.0 | 9261 | 0.6362 | 0.0 |
| 0.6538 | 50.0 | 9450 | 0.6361 | 0.0 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.12.0
- Tokenizers 0.13.3
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