---
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