---
license: mit
base_model: deepset/gbert-base
tags:
- generated_from_trainer
model-index:
- name: gbert-base-finetuned-twitter_
  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-finetuned-twitter_

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: 1.6651

## 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: 192
- eval_batch_size: 192
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.1933        | 1.0   | 4180  | 1.9612          |
| 2.0051        | 2.0   | 8360  | 1.8795          |
| 1.939         | 3.0   | 12540 | 1.8310          |
| 1.8928        | 4.0   | 16720 | 1.8013          |
| 1.8594        | 5.0   | 20900 | 1.7730          |
| 1.8336        | 6.0   | 25080 | 1.7702          |
| 1.8145        | 7.0   | 29260 | 1.7449          |
| 1.7963        | 8.0   | 33440 | 1.7277          |
| 1.7806        | 9.0   | 37620 | 1.7105          |
| 1.7682        | 10.0  | 41800 | 1.7061          |
| 1.7584        | 11.0  | 45980 | 1.7041          |
| 1.7454        | 12.0  | 50160 | 1.6899          |
| 1.7374        | 13.0  | 54340 | 1.6850          |
| 1.7295        | 14.0  | 58520 | 1.6856          |
| 1.7232        | 15.0  | 62700 | 1.6819          |
| 1.715         | 16.0  | 66880 | 1.6730          |
| 1.7101        | 17.0  | 71060 | 1.6723          |
| 1.7057        | 18.0  | 75240 | 1.6655          |
| 1.7038        | 19.0  | 79420 | 1.6617          |
| 1.702         | 20.0  | 83600 | 1.6625          |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3