modernbert-financial-sentiment

This model is a fine-tuned version of answerdotai/ModernBERT-base on the twitter_financial dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4501
  • Accuracy: 0.8558
  • F1: 0.8598
  • Precision: 0.8705
  • Recall: 0.8558

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
0.4274 1.0 1193 0.3893 0.8752 0.8787 0.8887 0.8752
0.2062 2.0 2386 0.4430 0.8928 0.8921 0.8918 0.8928

Framework versions

  • Transformers 4.49.0.dev0
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0
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