---
library_name: transformers
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: results
  results: []
datasets:
- ambile-official/AMBILE_Shah_Jo_Risalo_Labeled
language:
- sd
pipeline_tag: text-classification
---

<!-- 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. -->

# results

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7003
- Accuracy: 0.5660
- F1: 0.5571

## 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: 8
- eval_batch_size: 8
- 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
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 477  | 2.8092          | 0.2442   | 0.1739 |
| 2.961         | 2.0   | 954  | 2.4814          | 0.3187   | 0.2486 |
| 2.6582        | 3.0   | 1431 | 2.2660          | 0.3889   | 0.3370 |
| 2.3599        | 4.0   | 1908 | 2.0642          | 0.4277   | 0.3836 |
| 2.0474        | 5.0   | 2385 | 1.9820          | 0.4476   | 0.4212 |
| 1.7898        | 6.0   | 2862 | 1.9047          | 0.4738   | 0.4416 |
| 1.598         | 7.0   | 3339 | 1.7972          | 0.4937   | 0.4680 |
| 1.4538        | 8.0   | 3816 | 1.7815          | 0.5063   | 0.4805 |
| 1.2541        | 9.0   | 4293 | 1.7712          | 0.5199   | 0.4941 |
| 1.1149        | 10.0  | 4770 | 1.7398          | 0.5189   | 0.4950 |
| 0.9883        | 11.0  | 5247 | 1.7048          | 0.5304   | 0.5185 |
| 0.9024        | 12.0  | 5724 | 1.7161          | 0.5503   | 0.5390 |
| 0.7866        | 13.0  | 6201 | 1.6983          | 0.5535   | 0.5414 |
| 0.721         | 14.0  | 6678 | 1.7003          | 0.5660   | 0.5571 |
| 0.6566        | 15.0  | 7155 | 1.6980          | 0.5556   | 0.5492 |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0