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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: 0.2086
  • Accuracy: 0.9255
  • F1: 0.9257

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
0.8249 1.0 250 0.3042 0.9085 0.9068
0.2437 2.0 500 0.2086 0.9255 0.9257

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.10.1
  • Datasets 1.17.0
  • Tokenizers 0.10.3
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Dataset used to train Yaia/distilbert-base-uncased-finetuned-emotion

Evaluation results