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metadata
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

roberta-base-bne-finetuned-amazon_reviews_multi

This model is a fine-tuned version of 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