---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sentiment-roberta-es-2025-II
  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. -->

# sentiment-roberta-es-2025-II

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: 1.1261
- F1 Macro: 0.6714
- F1 Weighted: 0.6733
- Precision Macro: 0.6697
- Recall Macro: 0.6751
- Accuracy: 0.6770

## 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 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_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | Precision Macro | Recall Macro | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:---------------:|:------------:|:--------:|
| 1.0981        | 1.0   | 241  | 1.0390          | 0.4469   | 0.4554      | 0.3927          | 0.5369       | 0.5588   |
| 0.8394        | 2.0   | 482  | 0.7404          | 0.6780   | 0.6832      | 0.6829          | 0.6750       | 0.6826   |
| 0.6608        | 3.0   | 723  | 0.8494          | 0.6603   | 0.6635      | 0.6645          | 0.6762       | 0.6722   |
| 0.5192        | 4.0   | 964  | 0.7772          | 0.6869   | 0.6891      | 0.6889          | 0.6853       | 0.6889   |
| 0.4056        | 5.0   | 1205 | 0.8797          | 0.6879   | 0.6888      | 0.6969          | 0.6869       | 0.6847   |
| 0.327         | 6.0   | 1446 | 1.0902          | 0.6962   | 0.6998      | 0.6960          | 0.6980       | 0.7024   |
| 0.2616        | 7.0   | 1687 | 1.0482          | 0.6899   | 0.6923      | 0.6940          | 0.6874       | 0.6899   |
| 0.1981        | 8.0   | 1928 | 1.2889          | 0.6818   | 0.6834      | 0.6824          | 0.6897       | 0.6847   |
| 0.1452        | 9.0   | 2169 | 1.4574          | 0.6852   | 0.6876      | 0.6845          | 0.6874       | 0.6868   |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1