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distilbert-base-uncased-finetuned-emotion

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: 0.1560
  • Accuracy: 0.94
  • F1: 0.9403

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

Training Loss Epoch Step Validation Loss Accuracy F1
No log 1.0 1000 0.2056 0.928 0.9284
0.3151 2.0 2000 0.1560 0.94 0.9403

Framework versions

  • Transformers 4.21.3
  • Pytorch 1.10.2+cu102
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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Dataset used to train qsnell/distilbert-base-uncased-finetuned-emotion

Evaluation results