---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-large-touche-base-binary
  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-large-touche-base-binary

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7071
- Accuracy: 0.645
- Macro F1: 0.6430
- Fallacy F1: 0.6698

## 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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Fallacy F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:----------:|
| 1.3678        | 1.0   | 93   | 0.6908          | 0.515    | 0.3884   | 0.6667     |
| 1.2771        | 2.0   | 186  | 0.6375          | 0.65     | 0.6500   | 0.6465     |
| 1.3786        | 3.0   | 279  | 0.7071          | 0.645    | 0.6430   | 0.6698     |


### Framework versions

- Transformers 5.9.0
- Pytorch 2.11.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2