---
license: apache-2.0
base_model: BSC-TeMU/roberta-base-bne
tags:
- generated_from_trainer
datasets:
- multilingual-sentiments
metrics:
- accuracy
model-index:
- name: roberta-base-bne-finetuned-amazon_reviews_multi
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: multilingual-sentiments
      type: multilingual-sentiments
      config: spanish
      split: validation
      args: spanish
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6882716049382716
---

<!-- 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. -->

# roberta-base-bne-finetuned-amazon_reviews_multi

This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co./BSC-TeMU/roberta-base-bne) on the multilingual-sentiments dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6935
- Accuracy: 0.6883

## 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.786         | 1.0   | 115  | 0.6998          | 0.6914   |
| 0.474         | 2.0   | 230  | 0.6935          | 0.6883   |


### Framework versions

- Transformers 4.35.0
- Pytorch 1.13.1+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1