---
library_name: transformers
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: output_fp16
  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. -->

# output_fp16

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4230
- Accuracy: 0.8382

## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 8
- 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
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.5485        | 1.0   | 12272  | 0.4865          | 0.8100   |
| 0.4989        | 2.0   | 24544  | 0.4720          | 0.8193   |
| 0.4743        | 3.0   | 36816  | 0.5417          | 0.7859   |
| 0.4762        | 4.0   | 49088  | 0.4359          | 0.8313   |
| 0.4525        | 5.0   | 61360  | 0.4297          | 0.8365   |
| 0.4457        | 6.0   | 73632  | 0.4273          | 0.8398   |
| 0.4205        | 7.0   | 85904  | 0.4343          | 0.8321   |
| 0.4315        | 8.0   | 98176  | 0.4287          | 0.8357   |
| 0.4271        | 9.0   | 110448 | 0.4299          | 0.8394   |
| 0.4031        | 10.0  | 122720 | 0.4250          | 0.8353   |
| 0.4           | 11.0  | 134992 | 0.4401          | 0.8345   |
| 0.3899        | 12.0  | 147264 | 0.4178          | 0.8418   |
| 0.3921        | 13.0  | 159536 | 0.4313          | 0.8386   |
| 0.3849        | 14.0  | 171808 | 0.4212          | 0.8378   |
| 0.3777        | 15.0  | 184080 | 0.4230          | 0.8382   |


### Framework versions

- Transformers 4.53.2
- Pytorch 2.6.0+cu124
- Datasets 2.18.0
- Tokenizers 0.21.2