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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - emo
metrics:
  - accuracy
  - f1
model-index:
  - name: distilbert-base-uncased-finetuned-emotion
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: emo
          type: emo
          config: emo2019
          split: test
          args: emo2019
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8718460700671629
          - name: F1
            type: f1
            value: 0.8831861224754917

distilbert-base-uncased-finetuned-emotion

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

  • Loss: 0.3598
  • Accuracy: 0.8718
  • F1: 0.8832

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: 64
  • eval_batch_size: 64
  • 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
0.5285 1.0 472 0.3616 0.8673 0.8792
0.2833 2.0 944 0.3598 0.8718 0.8832

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.0.1+cu118
  • Datasets 1.16.1
  • Tokenizers 0.13.3