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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
  - precision
  - recall
model-index:
  - name: finetuned-sentiment-analysis-model
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: imdb
          type: imdb
          args: plain_text
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.909
          - name: Precision
            type: precision
            value: 0.8899803536345776
          - name: Recall
            type: recall
            value: 0.9282786885245902

finetuned-sentiment-analysis-model

This model is a fine-tuned version of distilbert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2868
  • Accuracy: 0.909
  • Precision: 0.8900
  • Recall: 0.9283

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

Framework versions

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