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End of training
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metadata
license: mit
base_model: nlptown/bert-base-multilingual-uncased-sentiment
tags:
  - generated_from_trainer
datasets:
  - amazon_reviews_multi
metrics:
  - accuracy
  - f1
model-index:
  - name: amazon-reviews-finetuning-distilbert-base-uncased
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: amazon_reviews_multi
          type: amazon_reviews_multi
          config: en
          split: validation
          args: en
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7703180212014135
          - name: F1
            type: f1
            value: 0.7271375381543915

amazon-reviews-finetuning-distilbert-base-uncased

This model is a fine-tuned version of nlptown/bert-base-multilingual-uncased-sentiment on the amazon_reviews_multi dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5859
  • Accuracy: 0.7703
  • F1: 0.7271

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: 32
  • eval_batch_size: 32
  • 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 F1
No log 1.0 188 0.5587 0.7756 0.7297
No log 2.0 376 0.5859 0.7703 0.7271

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.0
  • Datasets 2.14.6.dev0
  • Tokenizers 0.13.3