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financial-twhin-bert-large-7labels

This model is a fine-tuned version of Twitter/twhin-bert-large on financial tweets. It achieves the following results on the evaluation set:

  • Loss: 0.2960
  • Accuracy: 0.9023
  • F1: 0.9014

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: 2.1732582582331977e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 1203
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
1.0082 0.3272 1500 0.4766 0.8302 0.8179
0.4354 0.9817 4500 0.3823 0.8616 0.8532
0.3136 1.6361 7500 0.3266 0.8872 0.8902
0.246 2.2906 10500 0.3183 0.8976 0.8923
0.2173 2.9450 13500 0.2960 0.9023 0.9014

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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