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financial_sentiment_model

This model is a fine-tuned version of deepmind/language-perceiver on the financial_phrasebank dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3467
  • Recall: 0.8840
  • Accuracy: 0.8804
  • Precision: 0.8604

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
  • distributed_type: tpu
  • 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 Recall Accuracy Precision
0.4481 1.0 273 0.4035 0.8526 0.8433 0.7955
0.4069 2.0 546 0.4478 0.8683 0.8289 0.8123
0.2225 3.0 819 0.3167 0.8747 0.8680 0.8387
0.1245 4.0 1092 0.3467 0.8840 0.8804 0.8604

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.9.0+cu102
  • Datasets 1.17.0
  • Tokenizers 0.10.3
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Dataset used to train oandreae/financial_sentiment_model

Evaluation results