finetuned-breast_cancer_images
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Train Accuracy: 0.9025
- Train Loss: 0.0125
- Accuracy: 0.9589
- Loss: 0.0175
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 103
Training results
Training Loss | Epoch | Step | Accuracy | Loss | Validation Loss |
---|---|---|---|---|---|
No log | 5.06 | 200 | 0.9114 | 0.0241 | 0.0172 |
No log | 5.06 | 200 | 0.9114 | 0.0241 | 0.0172 |
No log | 10.13 | 400 | 0.9335 | 0.0209 | 0.0157 |
No log | 10.13 | 400 | 0.9335 | 0.0209 | 0.0157 |
No log | 15.19 | 600 | 0.9241 | 0.0189 | 0.0172 |
No log | 15.19 | 600 | 0.9241 | 0.0189 | 0.0172 |
No log | 20.25 | 800 | 0.9430 | 0.0182 | 0.0161 |
No log | 20.25 | 800 | 0.9430 | 0.0182 | 0.0161 |
No log | 25.32 | 1000 | 0.9399 | 0.0165 | 0.0186 |
No log | 25.32 | 1000 | 0.9399 | 0.0165 | 0.0186 |
No log | 30.38 | 1200 | 0.9557 | 0.0155 | 0.0137 |
No log | 30.38 | 1200 | 0.9557 | 0.0155 | 0.0137 |
No log | 35.44 | 1400 | 0.9335 | 0.0136 | 0.0180 |
No log | 35.44 | 1400 | 0.9335 | 0.0136 | 0.0180 |
No log | 40.51 | 1600 | 0.9525 | 0.0152 | 0.0139 |
No log | 40.51 | 1600 | 0.9525 | 0.0152 | 0.0139 |
No log | 45.57 | 1800 | 0.9494 | 0.0144 | 0.0149 |
No log | 45.57 | 1800 | 0.9494 | 0.0144 | 0.0149 |
No log | 50.63 | 2000 | 0.9430 | 0.0153 | 0.0187 |
No log | 50.63 | 2000 | 0.9430 | 0.0153 | 0.0187 |
No log | 55.7 | 2200 | 0.9557 | 0.0132 | 0.0149 |
No log | 55.7 | 2200 | 0.9557 | 0.0132 | 0.0149 |
No log | 60.76 | 2400 | 0.9430 | 0.0124 | 0.0149 |
No log | 60.76 | 2400 | 0.9430 | 0.0124 | 0.0149 |
No log | 65.82 | 2600 | 0.9525 | 0.0134 | 0.0164 |
No log | 65.82 | 2600 | 0.9525 | 0.0134 | 0.0164 |
No log | 70.89 | 2800 | 0.9557 | 0.0117 | 0.0143 |
No log | 70.89 | 2800 | 0.9557 | 0.0117 | 0.0143 |
No log | 75.95 | 3000 | 0.9557 | 0.0112 | 0.0166 |
No log | 75.95 | 3000 | 0.9557 | 0.0112 | 0.0166 |
No log | 81.01 | 3200 | 0.9589 | 0.0118 | 0.0163 |
No log | 81.01 | 3200 | 0.9589 | 0.0118 | 0.0163 |
No log | 86.08 | 3400 | 0.9494 | 0.0106 | 0.0188 |
No log | 86.08 | 3400 | 0.9494 | 0.0106 | 0.0188 |
No log | 91.14 | 3600 | 0.9462 | 0.0121 | 0.0186 |
No log | 91.14 | 3600 | 0.9462 | 0.0121 | 0.0186 |
No log | 96.2 | 3800 | 0.9525 | 0.0129 | 0.0171 |
No log | 96.2 | 3800 | 0.9525 | 0.0129 | 0.0171 |
No log | 101.27 | 4000 | 0.9589 | 0.0125 | 0.0175 |
No log | 101.27 | 4000 | 0.9589 | 0.0125 | 0.0175 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.3.0+cu121
- Tokenizers 0.13.3
- Downloads last month
- 2
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.