---
license: mit
base_model: digitalepidemiologylab/covid-twitter-bert-v2
tags:
- generated_from_trainer
metrics:
- f1
- recall
- precision
model-index:
- name: covid_bert-e3-b16-v2-w0.01-dev1
  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. -->

# covid_bert-e3-b16-v2-w0.01-dev1

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: 0.9608
- F1: 0.7913
- Recall: 0.7913
- Precision: 0.7913

## 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 | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|
| 0.8059        | 1.0   | 753  | 0.6912          | 0.7558 | 0.7558 | 0.7558    |
| 0.5563        | 2.0   | 1506 | 0.7618          | 0.7804 | 0.7804 | 0.7804    |
| 0.3678        | 3.0   | 2259 | 0.9608          | 0.7913 | 0.7913 | 0.7913    |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3