transformers pytorch tensorboard roberta text-classification generated_from_trainer dataset:amazon_reviews_multi license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- amazon_reviews_multi
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: gcapde-finetuned-amazon_reviews_multi
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: amazon_reviews_multi
      type: amazon_reviews_multi
      config: es
      split: validation
      args: es
    metrics:
    - type: accuracy
      value: 0.908
      name: Accuracy
---

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# gcapde-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: 0.2896
- Accuracy: 0.908

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2333        | 1.0   | 63   | 0.2837          | 0.9002   |
| 0.2117        | 2.0   | 126  | 0.2896          | 0.908    |


### Framework versions

- Transformers 4.27.2
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
