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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - amazon_reviews_multi
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: selectra-small-finetuned-amazon-review
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: amazon_reviews_multi
          type: amazon_reviews_multi
          args: es
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.737
          - name: F1
            type: f1
            value: 0.7437773019932409
          - name: Precision
            type: precision
            value: 0.7524857881639091
          - name: Recall
            type: recall
            value: 0.737

selectra-small-finetuned-amazon-review

This model is a fine-tuned version of Recognai/selectra_small on the amazon_reviews_multi dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6279
  • Accuracy: 0.737
  • F1: 0.7438
  • Precision: 0.7525
  • Recall: 0.737

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: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
No log 0.5 500 0.7041 0.7178 0.6724 0.6715 0.7178
0.7908 1.0 1000 0.6365 0.7356 0.7272 0.7211 0.7356
0.7908 1.5 1500 0.6204 0.7376 0.7380 0.7387 0.7376
0.6358 2.0 2000 0.6162 0.7386 0.7377 0.7380 0.7386
0.6358 2.5 2500 0.6228 0.7274 0.7390 0.7576 0.7274
0.5827 3.0 3000 0.6188 0.7378 0.7400 0.7425 0.7378
0.5827 3.5 3500 0.6246 0.7374 0.7416 0.7467 0.7374
0.5427 4.0 4000 0.6266 0.7446 0.7452 0.7465 0.7446
0.5427 4.5 4500 0.6331 0.7392 0.7421 0.7456 0.7392
0.5184 5.0 5000 0.6279 0.737 0.7438 0.7525 0.737

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.10.0+cu111
  • Datasets 1.17.0
  • Tokenizers 0.10.3