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---
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: 0.5651
- F1 Macro: 0.6566
- F1 Misinformation: 0.9336
- F1 Factual: 0.8316
- F1 Other: 0.2048
- Prec Macro: 0.6775
- Prec Misinformation: 0.9344
- Prec Factual: 0.7907
- Prec Other: 0.3075
## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 4367
- num_epochs: 60
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Misinformation | F1 Factual | F1 Other | Prec Macro | Prec Misinformation | Prec Factual | Prec Other |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:----------:|:--------:|:----------:|:-------------------:|:------------:|:----------:|
| 0.5055 | 3.67 | 500 | 0.3267 | 0.6006 | 0.9440 | 0.8517 | 0.0062 | 0.8132 | 0.9228 | 0.8502 | 0.6667 |
| 0.0876 | 7.35 | 1000 | 0.3922 | 0.6636 | 0.9412 | 0.8533 | 0.1963 | 0.6975 | 0.9255 | 0.8729 | 0.2941 |
| 0.0477 | 11.03 | 1500 | 0.4479 | 0.6715 | 0.9404 | 0.8562 | 0.2178 | 0.6939 | 0.9288 | 0.8695 | 0.2836 |
| 0.0334 | 14.7 | 2000 | 0.5123 | 0.6622 | 0.9418 | 0.8515 | 0.1935 | 0.6996 | 0.9251 | 0.8732 | 0.3007 |
| 0.0271 | 18.38 | 2500 | 0.5651 | 0.6566 | 0.9336 | 0.8316 | 0.2048 | 0.6775 | 0.9344 | 0.7907 | 0.3075 |
### Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.2
- Tokenizers 0.13.1
|