This model is a fine-tuned version of nvidia/mit-b0 on the as-cle-bert/breastcancer-semantic-segmentation dataset. It achieves the following results on the evaluation set:

Loss: 1.2330
Mean Iou: 0.3012
Mean Accuracy: 0.5964
Overall Accuracy: 0.8331
Accuracy Background: nan
Accuracy Benign Breast Cancer: 0.1308
Accuracy Malignant Breast Cancer: 0.8042
Accuracy Ignore: 0.8543
Iou Background: 0.0
Iou Benign Breast Cancer: 0.0749
Iou Malignant Breast Cancer: 0.2943
Iou Ignore: 0.8356

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: 6e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Accuracy Background	Accuracy Benign Breast Cancer	Accuracy Malignant Breast Cancer	Accuracy Ignore	Iou Background	Iou Benign Breast Cancer	Iou Malignant Breast Cancer	Iou Ignore
1.1649	0.625	10	1.2330	0.3012	0.5964	0.8331	nan	0.1308	0.8042	0.8543	0.0	0.0749	0.2943	0.8356

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cpu
Datasets 3.0.0
Tokenizers 0.19.1

PushkarA07/segformer-b0-finetuned-breastcancer-oct-22

segformer-b0-finetuned-breastcancer-oct-22

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

PushkarA07/
segformer-b0-finetuned-breastcancer-oct-22