---
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: 1.7380

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.194         | 1.0   | 4180  | 1.9622          |
| 2.0075        | 2.0   | 8360  | 1.8813          |
| 1.9429        | 3.0   | 12540 | 1.8339          |
| 1.8985        | 4.0   | 16720 | 1.8057          |
| 1.8676        | 5.0   | 20900 | 1.7801          |
| 1.8446        | 6.0   | 25080 | 1.7793          |
| 1.829         | 7.0   | 29260 | 1.7580          |
| 1.815         | 8.0   | 33440 | 1.7445          |
| 1.8048        | 9.0   | 37620 | 1.7319          |
| 1.7997        | 10.0  | 41800 | 1.7331          |


### Framework versions

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