---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: covid-augment-tweet-bert-large-e4
  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-e4

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: 0.3723
- Accuracy: 0.9587
- F1: 0.8889
- Precision: 0.8920
- Recall: 0.8858

## 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: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1307        | 1.0   | 4089  | 0.3055          | 0.9523   | 0.8771 | 0.8435    | 0.9135 |
| 0.0367        | 2.0   | 8178  | 0.3270          | 0.9568   | 0.8885 | 0.8558    | 0.9239 |
| 0.0133        | 3.0   | 12267 | 0.3316          | 0.9600   | 0.8949 | 0.8771    | 0.9135 |
| 0.0007        | 4.0   | 16356 | 0.3723          | 0.9587   | 0.8889 | 0.8920    | 0.8858 |


### Framework versions

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