finbert_fx_sentiment_runs

This model is a fine-tuned version of distilbert-base-uncased on the financial_phrasebank dataset. It achieves the following results on the evaluation set:

• Loss: 0.1182
• Accuracy: 0.95
• F1 Macro: 0.9317

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: 64
• seed: 42
• optimizer: Use OptimizerNames.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: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro
No log	1.0	99	0.2899	0.8971	0.8501
No log	2.0	198	0.1299	0.9618	0.9427
No log	3.0	297	0.1182	0.95	0.9317

Framework versions

• Transformers 4.57.6
• Pytorch 2.11.0+cu130
• Datasets 2.21.0
• Tokenizers 0.22.2