finbert-tone-finetuned-fintwitter-classification

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finbert-tone-finetuned-fintwitter-classification

This model is a fine-tuned version of yiyanghkust/finbert-tone on Twitter Financial News dataset. It achieves the following results on the evaluation set:

• Loss: 1.4078
• Accuracy: 0.8840
• F1: 0.8838
• Precision: 0.8838
• Recall: 0.8840

Model description

Model determines the financial sentiment of given tweets. Given the unbalanced distribution of the class labels, the weights were adjusted to pay attention to the less sampled labels which should increase overall performance..

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: 20
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0+cu116
• Datasets 2.8.0
• Tokenizers 0.13.2