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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - emotion
model-index:
  - name: distilbert-base-uncased-fine-tuned-emotions
    results: []

distilbert-base-uncased-fine-tuned-emotions

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

  • Loss: 0.2433
  • Acc : 0.9355
  • F1 : 0.9356

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: 10

Training results

Training Loss Epoch Step Validation Loss Acc F1
0.1674 1.0 250 0.1948 0.9275 0.9267
0.1185 2.0 500 0.1635 0.938 0.9380
0.0998 3.0 750 0.1723 0.9345 0.9352
0.0808 4.0 1000 0.1687 0.934 0.9337
0.0621 5.0 1250 0.1769 0.937 0.9368
0.0511 6.0 1500 0.1927 0.933 0.9327
0.0393 7.0 1750 0.2275 0.9345 0.9348
0.0323 8.0 2000 0.2338 0.932 0.9324
0.0273 9.0 2250 0.2439 0.935 0.9352
0.0215 10.0 2500 0.2433 0.9355 0.9356

Framework versions

  • Transformers 4.27.2
  • Pytorch 1.13.1+cu117
  • Datasets 2.11.0
  • Tokenizers 0.13.3