transformers tensorboard safetensors roberta text-classification generated_from_trainer base_model:FacebookAI/xlm-roberta-base base_model:finetune:FacebookAI/xlm-roberta-base license:mit autotrain_compatible endpoints_compatible region:us
---
base_model: FacebookAI/xlm-roberta-base
license: mit
metrics:
- pearsonr
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-finetuned-translation
  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. -->

# xlm-roberta-base-finetuned-translation

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0497
- Pearsonr: 0.8316

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pearsonr |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0836        | 1.0   | 296  | 0.1106          | 0.8231   |
| 0.0512        | 2.0   | 592  | 0.0512          | 0.8233   |
| 0.052         | 3.0   | 888  | 0.0597          | 0.8255   |
| 0.0466        | 4.0   | 1184 | 0.0539          | 0.8208   |
| 0.0535        | 5.0   | 1480 | 0.0485          | 0.8291   |
| 0.0477        | 6.0   | 1776 | 0.0479          | 0.8306   |
| 0.0432        | 7.0   | 2072 | 0.0497          | 0.8316   |
| 0.0495        | 8.0   | 2368 | 0.0490          | 0.8290   |
| 0.0454        | 9.0   | 2664 | 0.0492          | 0.8262   |
| 0.0496        | 10.0  | 2960 | 0.0503          | 0.8239   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
