pytorch bert text-classification transformers generated_from_trainer license:mit model-index
---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: covid-twitter-bert-v2-with_description-stance
  results: []
---

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# covid-twitter-bert-v2-with_description-stance

This model is a fine-tuned version of [digitalepidemiologylab/covid-twitter-bert-v2](https://huggingface.co/digitalepidemiologylab/covid-twitter-bert-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6433
- Accuracy: 0.2486

## 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: 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9001        | 1.0   | 632  | 0.6433          | 0.2486   |
| 0.6247        | 2.0   | 1264 | 0.5531          | 0.0829   |
| 0.4811        | 3.0   | 1896 | 0.6068          | 0.0694   |
| 0.2546        | 4.0   | 2528 | 0.7426          | 0.0414   |
| 0.1365        | 5.0   | 3160 | 0.8197          | 0.0392   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.4.0
- Tokenizers 0.12.1
