---
license: mit
tags:
- generated_from_trainer
model-index:
- name: mlcovid19-classifier
  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. -->

# mlcovid19-classifier

This model is a fine-tuned version of [oscarwu/mlcovid19-classifier](https://huggingface.co/oscarwu/mlcovid19-classifier) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4565
- F1 Macro: 0.6596
- F1 Misinformation: 0.8776
- F1 Factual: 0.8823
- F1 Other: 0.2188
- Prec Macro: 0.7181
- Prec Misinformation: 0.834
- Prec Factual: 0.8952
- Prec Other: 0.4251

## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2165
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Misinformation | F1 Factual | F1 Other | Prec Macro | Prec Misinformation | Prec Factual | Prec Other |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:----------:|:--------:|:----------:|:-------------------:|:------------:|:----------:|
| 1.1986        | 0.94  | 16   | 1.0988          | 0.6120   | 0.8270            | 0.7623     | 0.2466   | 0.6567     | 0.7636              | 0.8578       | 0.3487     |
| 1.1885        | 1.94  | 32   | 1.0851          | 0.6163   | 0.8271            | 0.7645     | 0.2574   | 0.6588     | 0.7660              | 0.8557       | 0.3547     |
| 1.1538        | 2.94  | 48   | 1.0625          | 0.6198   | 0.8275            | 0.7683     | 0.2635   | 0.6593     | 0.7695              | 0.8521       | 0.3565     |
| 1.1386        | 3.94  | 64   | 1.0307          | 0.6235   | 0.8259            | 0.7722     | 0.2725   | 0.6564     | 0.7738              | 0.8452       | 0.3502     |
| 1.0935        | 4.94  | 80   | 0.9911          | 0.6276   | 0.8259            | 0.7797     | 0.2771   | 0.6549     | 0.7803              | 0.8392       | 0.3452     |
| 1.055         | 5.94  | 96   | 0.9445          | 0.6304   | 0.8271            | 0.7912     | 0.2730   | 0.6521     | 0.7893              | 0.8344       | 0.3327     |
| 0.9925        | 6.94  | 112  | 0.8945          | 0.6340   | 0.8270            | 0.8001     | 0.2749   | 0.6518     | 0.7976              | 0.8251       | 0.3327     |
| 0.9446        | 7.94  | 128  | 0.8448          | 0.6390   | 0.8303            | 0.8106     | 0.2760   | 0.6545     | 0.8088              | 0.8186       | 0.3360     |
| 0.8813        | 8.94  | 144  | 0.7970          | 0.6448   | 0.8355            | 0.8238     | 0.2752   | 0.6598     | 0.8185              | 0.8214       | 0.3395     |
| 0.8259        | 9.94  | 160  | 0.7475          | 0.6480   | 0.8405            | 0.8330     | 0.2704   | 0.6644     | 0.8243              | 0.8256       | 0.3434     |
| 0.7721        | 10.94 | 176  | 0.6971          | 0.6532   | 0.8483            | 0.8430     | 0.2684   | 0.6746     | 0.8281              | 0.8375       | 0.3583     |
| 0.7107        | 11.94 | 192  | 0.6542          | 0.6510   | 0.8527            | 0.8496     | 0.2507   | 0.6765     | 0.8290              | 0.8448       | 0.3557     |
| 0.6742        | 12.94 | 208  | 0.6126          | 0.6527   | 0.8554            | 0.8544     | 0.2484   | 0.6793     | 0.8298              | 0.8521       | 0.3560     |
| 0.6296        | 13.94 | 224  | 0.5735          | 0.6560   | 0.8603            | 0.8586     | 0.2491   | 0.6902     | 0.8298              | 0.8602       | 0.3804     |
| 0.5947        | 14.94 | 240  | 0.5416          | 0.6592   | 0.8641            | 0.8624     | 0.2512   | 0.6986     | 0.8299              | 0.8689       | 0.3970     |
| 0.5728        | 15.94 | 256  | 0.5164          | 0.6584   | 0.8678            | 0.8674     | 0.2402   | 0.7028     | 0.8312              | 0.8745       | 0.4026     |
| 0.5424        | 16.94 | 272  | 0.4950          | 0.6620   | 0.8711            | 0.8720     | 0.2428   | 0.7110     | 0.8315              | 0.8836       | 0.4178     |
| 0.5277        | 17.94 | 288  | 0.4798          | 0.6594   | 0.8727            | 0.8751     | 0.2305   | 0.7107     | 0.8316              | 0.8874       | 0.4130     |
| 0.5204        | 18.94 | 304  | 0.4679          | 0.6613   | 0.8749            | 0.8767     | 0.2323   | 0.7183     | 0.8335              | 0.8868       | 0.4346     |
| 0.5061        | 19.94 | 320  | 0.4565          | 0.6596   | 0.8776            | 0.8823     | 0.2188   | 0.7181     | 0.834               | 0.8952       | 0.4251     |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1