---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: roberta-base-detect-cheapfake-combined-train-test-contradict-2-8
  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. -->

# roberta-base-detect-cheapfake-combined-train-test-contradict-2-8

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: 0.5226
- Accuracy: 0.835
- F1: 0.8156

## 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: 5e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 163  | 0.7064          | 0.64     | 0.5385 |
| No log        | 2.0   | 326  | 0.5252          | 0.765    | 0.7662 |
| No log        | 3.0   | 489  | 0.4988          | 0.82     | 0.8269 |
| 0.1701        | 4.0   | 652  | 0.6552          | 0.77     | 0.7125 |
| 0.1701        | 5.0   | 815  | 0.5226          | 0.835    | 0.8156 |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1