---
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: 1.1992
- F1: 0.4000

## 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: 4e-06
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.6664        | 1.0   | 189  | 0.6660          | 0.0    |
| 0.5942        | 2.0   | 378  | 0.5671          | 0.3750 |
| 0.5593        | 3.0   | 567  | 0.8488          | 0.3111 |
| 0.6282        | 4.0   | 756  | 0.6896          | 0.4444 |
| 0.558         | 5.0   | 945  | 0.8825          | 0.4167 |
| 0.5242        | 6.0   | 1134 | 1.0105          | 0.3774 |
| 0.4843        | 7.0   | 1323 | 1.1065          | 0.4082 |
| 0.3792        | 8.0   | 1512 | 1.1807          | 0.4    |
| 0.4005        | 9.0   | 1701 | 1.2279          | 0.3774 |
| 0.3909        | 10.0  | 1890 | 1.1992          | 0.4000 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.12.0
- Tokenizers 0.13.3