---
license: mit
base_model: digitalepidemiologylab/covid-twitter-bert-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: covid-twitter-bert-v2_epoch3_batch4_lr2e-05_w0.01
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# covid-twitter-bert-v2_epoch3_batch4_lr2e-05_w0.01

This model is a fine-tuned version of [digitalepidemiologylab/covid-twitter-bert-v2](https://huggingface.co/digitalepidemiologylab/covid-twitter-bert-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5108
- Accuracy: 0.7497
- F1: 0.6879
- Precision: 0.6425
- Recall: 0.7403

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6731        | 1.0   | 788  | 0.6654          | 0.6274   | 0.0    | 0.0       | 0.0    |
| 0.6727        | 2.0   | 1576 | 0.6396          | 0.6274   | 0.0    | 0.0       | 0.0    |
| 0.6462        | 3.0   | 2364 | 0.5108          | 0.7497   | 0.6879 | 0.6425    | 0.7403 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3