---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: covid-augment-tweet-bert-large-e2-v2
  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-augment-tweet-bert-large-e2-v2

This model is a fine-tuned version of [digitalepidemiologylab/covid-twitter-bert](https://huggingface.co/digitalepidemiologylab/covid-twitter-bert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2513
- Accuracy: 0.9639
- F1: 0.9051
- Precision: 0.8870
- Recall: 0.9239

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0495        | 1.0   | 1023 | 0.2682          | 0.9600   | 0.8920 | 0.8982    | 0.8858 |
| 0.0135        | 2.0   | 2046 | 0.2513          | 0.9639   | 0.9051 | 0.8870    | 0.9239 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3