SmolLM-1.7B-heart

• Loss: 0.5127
• Accuracy: 0.7833
• Report: precision recall f1-score support
  absence 0.77 0.82 0.79 92 presence 0.80 0.75 0.77 88
  accuracy 0.78 180 macro avg 0.78 0.78 0.78 180 weighted avg 0.78 0.78 0.78 180

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

• learning_rate: 2e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 5

Training results

 absence       0.66      0.85      0.74        92
presence       0.77      0.55      0.64        88

accuracy                           0.70       180

 absence       0.74      0.82      0.77        92
presence       0.78      0.69      0.73        88

accuracy                           0.76       180

 absence       0.74      0.82      0.77        92
presence       0.78      0.69      0.73        88

accuracy                           0.76       180

 absence       0.75      0.82      0.78        92
presence       0.79      0.72      0.75        88

accuracy                           0.77       180

 absence       0.77      0.82      0.79        92
presence       0.80      0.75      0.77        88

accuracy                           0.78       180

Framework versions

• PEFT 0.15.2
• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 2.14.4
• Tokenizers 0.21.1