---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
model-index:
- name: relex_pre
  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. -->

# relex_pre

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4173
- Macro F1: 0.9040

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Macro F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8776        | 1.0   | 1328 | 0.3809          | 0.7517   |
| 0.2962        | 2.0   | 2656 | 0.3053          | 0.8606   |
| 0.2057        | 3.0   | 3984 | 0.3026          | 0.8932   |
| 0.1408        | 4.0   | 5312 | 0.3286          | 0.9079   |
| 0.0961        | 5.0   | 6640 | 0.4013          | 0.8945   |
| 0.0628        | 6.0   | 7968 | 0.4145          | 0.9037   |
| 0.042         | 7.0   | 9296 | 0.4173          | 0.9040   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1