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

# entex_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: 0.2082
- F1 Macro: 0.8500

## 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-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 | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0679        | 1.0   | 26   | 0.5775          | 0.2761   |
| 0.3311        | 2.0   | 52   | 0.2341          | 0.7785   |
| 0.186         | 3.0   | 78   | 0.2036          | 0.8220   |
| 0.1366        | 4.0   | 104  | 0.1852          | 0.8459   |
| 0.1003        | 5.0   | 130  | 0.1907          | 0.8516   |
| 0.0793        | 6.0   | 156  | 0.2027          | 0.8486   |
| 0.0668        | 7.0   | 182  | 0.2082          | 0.8500   |


### Framework versions

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