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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: 0.5500
  • F1: 0.8386
  • Accuracy: 0.8528

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
  • train_batch_size: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss F1 Accuracy
0.6031 0.94 100 0.3779 0.8373 0.8501
0.2667 1.89 200 0.4195 0.8408 0.8638
0.1264 2.83 300 0.4813 0.8459 0.8666
0.0582 3.77 400 0.5500 0.8386 0.8528

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.1.0
  • Datasets 2.14.5
  • Tokenizers 0.14.1
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Finetuned from

Dataset used to train jessica-ecosia/phrasebank-sentiment-analysis

Evaluation results