---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base-pan-clef-subtask2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# roberta-base-pan-clef-subtask2

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: 3.4936
- Micro F1: 0.5654
- Macro F1: 0.6413
- Macro Recall: 0.7827
- Accuracy: 0.5654

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Micro F1 | Macro F1 | Macro Recall | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:------------:|:--------:|
| 0.1032        | 1.0    | 4515 | 3.0365          | 0.5613   | 0.6005   | 0.7793       | 0.5613   |
| 0.0501        | 1.9997 | 9028 | 3.4936          | 0.5654   | 0.6413   | 0.7827       | 0.5654   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1