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fredriko/phrasebank-sentiment-analysis

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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Model Card

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phrasebank-sentiment-analysis

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

  • Loss: 0.5575
  • F1: 0.8315
  • Accuracy: 0.8514

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: 5e-05
  • trainbatchsize: 32
  • evalbatchsize: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 4

Training results

Training LossEpochStepValidation LossF1Accuracy
0.55170.941000.37970.83560.8604
0.26541.892000.42900.82880.8549
0.1342.833000.47760.83440.8549
0.05943.774000.55750.83150.8514

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1