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Dataset2-SwinV2 – AI Model by Nicole-M | AlphaNeural AI
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Dataset2-SwinV2
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safetensors
swinv2
image-classification
breast cancer
generated_from_trainer
us
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swinV2-CBIS
This model is a fine-tuned version of
swinv2
on the CBIS-DDSM dataset. It achieves the following results on the evaluation set:
Loss: 0.6876
Accuracy: 0.6085
Precision: 0.3702
Recall: 0.6085
F1: 0.4604
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: 3e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.7205
1.0
165
0.6842
0.6085
0.3702
0.6085
0.4604
0.6924
2.0
330
0.6847
0.6085
0.3702
0.6085
0.4604
0.6867
3.0
495
0.6876
0.6085
0.3702
0.6085
0.4604
Framework versions
Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.21.0
Tokenizers 0.19.1
