| --- |
| library_name: PyTorch |
| tags: |
| - maternal |
| - CNN |
| - Image classification |
| - Research only |
| metrics: |
| - accuracy |
| - recall |
| - precision |
| - f1_score |
| model-index: |
| - name: FP_Classifcation-V1 |
| results: |
| - task: |
| type: image-classification |
| dataset: |
| type: Marc-HealthAI/fetal-planes-classification-dataset-main |
| name: fetal-planes-classification-dataset-main |
| metrics: |
| - type: recall |
| value: 0.9098 |
| name: Recall macro |
| --- |
| |
| # FP_Classifcation-V1 |
| |
| This model was trained from scratch on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| <!-- START_EVAL_SUMMARY --> |
| - Loss: 0.2940 |
| - Accuracy: 0.9026 |
| - Precision Macro: 0.8742 |
| - Recall Macro: 0.9098 |
| - F1 Macro: 0.8895 |
| <!-- END_EVAL_SUMMARY --> |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| <!-- START_TRAINING_RESULTS --> |
| The following hyperparameters were used during training: |
| - learning_rate: 0.001 |
| - train_batch_size: 4 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 16 |
| - 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: cosine |
| - num_epochs: 50 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------------:|:------------:|:--------:| |
| | 1.0869 | 1.0 | 483 | 0.7657 | 0.6792 | 0.6837 | 0.7053 | 0.6710 | |
| | 0.9801 | 2.0 | 966 | 0.7458 | 0.7507 | 0.7370 | 0.7004 | 0.7055 | |
| | 0.9227 | 3.0 | 1449 | 0.6545 | 0.7143 | 0.7075 | 0.7831 | 0.6999 | |
| | 0.7036 | 4.0 | 1932 | 0.5989 | 0.7733 | 0.7476 | 0.8058 | 0.7593 | |
| | 0.6729 | 5.0 | 2415 | 0.5175 | 0.7830 | 0.7617 | 0.8409 | 0.7753 | |
| | 0.8200 | 6.0 | 2898 | 0.4929 | 0.7863 | 0.7541 | 0.8398 | 0.7735 | |
| | 0.7750 | 7.0 | 3381 | 0.4570 | 0.8154 | 0.7830 | 0.8476 | 0.8038 | |
| | 0.8015 | 8.0 | 3864 | 0.4494 | 0.8384 | 0.8090 | 0.8493 | 0.8243 | |
| | 0.6326 | 9.0 | 4347 | 0.4928 | 0.8263 | 0.8066 | 0.8151 | 0.8039 | |
| | 0.7675 | 10.0 | 4830 | 0.4397 | 0.8347 | 0.8021 | 0.8591 | 0.8175 | |
| | 0.6092 | 11.0 | 5313 | 0.4220 | 0.8554 | 0.8220 | 0.8603 | 0.8352 | |
| | 0.4704 | 12.0 | 5796 | 0.5017 | 0.8489 | 0.8190 | 0.8564 | 0.8321 | |
| | 0.6863 | 13.0 | 6279 | 0.4050 | 0.8533 | 0.8123 | 0.8687 | 0.8313 | |
| | 0.5217 | 14.0 | 6762 | 0.3839 | 0.8473 | 0.8123 | 0.8753 | 0.8296 | |
| | 0.4879 | 15.0 | 7245 | 0.4319 | 0.8687 | 0.8556 | 0.8531 | 0.8527 | |
| | 0.5894 | 16.0 | 7728 | 0.4071 | 0.8339 | 0.8098 | 0.8596 | 0.8245 | |
| | 0.4710 | 17.0 | 8211 | 0.3890 | 0.8622 | 0.8350 | 0.8626 | 0.8453 | |
| | 0.6325 | 18.0 | 8694 | 0.3555 | 0.8768 | 0.8425 | 0.8848 | 0.8589 | |
| | 0.6084 | 19.0 | 9177 | 0.3408 | 0.8865 | 0.8524 | 0.8901 | 0.8680 | |
| | 0.5211 | 20.0 | 9660 | 0.3399 | 0.8812 | 0.8484 | 0.8828 | 0.8627 | |
| | 0.3481 | 21.0 | 10143 | 0.3592 | 0.8905 | 0.8673 | 0.8818 | 0.8733 | |
| | 0.6450 | 22.0 | 10626 | 0.3644 | 0.8877 | 0.8632 | 0.8799 | 0.8706 | |
| | 0.4031 | 23.0 | 11109 | 0.3248 | 0.8962 | 0.8704 | 0.8944 | 0.8813 | |
| | 0.4193 | 24.0 | 11592 | 0.3284 | 0.8836 | 0.8587 | 0.8806 | 0.8677 | |
| | 0.4325 | 25.0 | 12075 | 0.3051 | 0.8881 | 0.8622 | 0.8958 | 0.8767 | |
| | 0.3674 | 26.0 | 12558 | 0.3227 | 0.8861 | 0.8626 | 0.8839 | 0.8713 | |
| | 0.3794 | 27.0 | 13041 | 0.3084 | 0.8982 | 0.8777 | 0.8920 | 0.8844 | |
| | 0.3150 | 28.0 | 13524 | 0.3058 | 0.8954 | 0.8680 | 0.8913 | 0.8777 | |
| | 0.4406 | 29.0 | 14007 | 0.2965 | 0.8877 | 0.8552 | 0.8943 | 0.8700 | |
| | 0.5185 | 30.0 | 14490 | 0.2986 | 0.9018 | 0.8768 | 0.8992 | 0.8868 | |
| | 0.5979 | 31.0 | 14973 | 0.3107 | 0.8986 | 0.8741 | 0.8921 | 0.8824 | |
| | 0.4205 | 32.0 | 15456 | 0.3153 | 0.9018 | 0.8760 | 0.9054 | 0.8882 | |
| | 0.3071 | 33.0 | 15939 | 0.2935 | 0.9010 | 0.8774 | 0.8998 | 0.8873 | |
| | 0.2884 | 34.0 | 16422 | 0.2940 | 0.9026 | 0.8742 | 0.9098 | 0.8895 | |
| | 0.3953 | 35.0 | 16905 | 0.3187 | 0.8970 | 0.8743 | 0.8911 | 0.8808 | |
| | 0.2838 | 36.0 | 17388 | 0.3100 | 0.9059 | 0.8814 | 0.8995 | 0.8896 | |
| | 0.3631 | 37.0 | 17871 | 0.3186 | 0.9063 | 0.8841 | 0.9014 | 0.8920 | |
| | 0.2681 | 38.0 | 18354 | 0.2929 | 0.9087 | 0.8841 | 0.9093 | 0.8951 | |
| | 0.2766 | 39.0 | 18837 | 0.2944 | 0.9022 | 0.8793 | 0.9006 | 0.8890 | |
| |
| <!-- END_TRAINING_RESULTS --> |
| |
| ### Framework versions |
| |
| - Transformers 5.17.0 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 5.0.1 |
| - Tokenizers 0.23.1 |
| |
