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-no_description-stance
  results: []
---

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# covid-twitter-bert-v2-no_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: 0.5898
- Accuracy: 0.1814

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8009        | 1.0   | 632  | 0.5898          | 0.1814   |
| 0.5663        | 2.0   | 1264 | 0.5613          | 0.0750   |
| 0.394         | 3.0   | 1896 | 0.6726          | 0.0347   |
| 0.1677        | 4.0   | 2528 | 0.8051          | 0.0269   |
| 0.08          | 5.0   | 3160 | 0.8690          | 0.0202   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu102
- Datasets 2.2.1
- Tokenizers 0.12.1
