pytorch tensorboard roberta text-classification dataset:amazon_reviews_multi transformers generated_from_trainer license:cc-by-4.0
---
license: cc-by-4.0
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
metrics:
- accuracy
model_index:
- name: roberta-base-bne-finetuned-amazon_reviews_multi
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: amazon_reviews_multi
      type: amazon_reviews_multi
      args: es
    metric:
      name: Accuracy
      type: accuracy
      value: 0.93075
---

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# 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 amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2306
- Accuracy: 0.9307

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1978        | 1.0   | 1250 | 0.1750          | 0.9325   |
| 0.0951        | 2.0   | 2500 | 0.2306          | 0.9307   |


### Framework versions

- Transformers 4.9.2
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3
