---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: DSC_xlm-roberta-large_finetuned
  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. -->

# DSC_xlm-roberta-large_finetuned

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: 1.0981
- Accuracy: 0.35
- F1 Macro: 0.1728

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 100
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 1.1194        | 1.0   | 350  | 1.1025          | 0.3293   | 0.1651   |
| 1.1063        | 2.0   | 700  | 1.0981          | 0.35     | 0.1728   |
| 1.1026        | 3.0   | 1050 | 1.0987          | 0.35     | 0.1728   |
| 1.1043        | 4.0   | 1400 | 1.0986          | 0.35     | 0.1728   |
| 1.1023        | 5.0   | 1750 | 1.1013          | 0.35     | 0.1728   |
| 1.1025        | 6.0   | 2100 | 1.0996          | 0.3293   | 0.1651   |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2