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

# verdict-classifier-trinary

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1258
- F1 Macro: 0.8408
- F1 Misinformation: 0.9751
- F1 Factual: 0.9508
- F1 Other: 0.5965
- Prec Macro: 0.8323
- Prec Misinformation: 0.9818
- Prec Factual: 1.0
- Prec Other: 0.5152

## 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
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 462
- num_epochs: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Misinformation | F1 Factual | F1 Other | Prec Macro | Prec Misinformation | Prec Factual | Prec Other |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:----------:|:--------:|:----------:|:-------------------:|:------------:|:----------:|
| 1.034         | 0.98  | 57   | 0.9960          | 0.3136   | 0.9408            | 0.0        | 0.0      | 0.2961     | 0.8882              | 0.0          | 0.0        |
| 0.968         | 1.98  | 114  | 0.8945          | 0.3136   | 0.9408            | 0.0        | 0.0      | 0.2961     | 0.8882              | 0.0          | 0.0        |
| 0.9253        | 2.98  | 171  | 0.7182          | 0.3136   | 0.9408            | 0.0        | 0.0      | 0.2961     | 0.8882              | 0.0          | 0.0        |
| 0.8215        | 3.98  | 228  | 0.3112          | 0.4795   | 0.9454            | 0.0        | 0.4932   | 0.4351     | 0.9381              | 0.0          | 0.3673     |
| 0.5073        | 4.98  | 285  | 0.1564          | 0.8272   | 0.9703            | 0.9355     | 0.5758   | 0.8025     | 0.9883              | 0.9667       | 0.4524     |
| 0.3046        | 5.98  | 342  | 0.1258          | 0.8408   | 0.9751            | 0.9508     | 0.5965   | 0.8323     | 0.9818              | 1.0          | 0.5152     |
| 0.1971        | 6.98  | 399  | 0.1540          | 0.8458   | 0.9796            | 0.9538     | 0.6038   | 0.8258     | 0.9863              | 0.9394       | 0.5517     |
| 0.1494        | 7.98  | 456  | 0.1779          | 0.8504   | 0.9737            | 0.9524     | 0.625    | 0.8195     | 0.9907              | 0.9677       | 0.5        |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu102
- Datasets 1.9.0
- Tokenizers 0.10.2