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---
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
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