# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ahmedesmail16/Psoriasis-Project-Aug-M2-beit-base-patch16-224-pt22k-ft22k")
model = AutoModelForImageClassification.from_pretrained("ahmedesmail16/Psoriasis-Project-Aug-M2-beit-base-patch16-224-pt22k-ft22k", device_map="auto")Quick Links
Psoriasis-Project-Aug-M2-beit-base-patch16-224-pt22k-ft22k
This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0042
- Accuracy: 1.0
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1065 | 0.99 | 36 | 0.3867 | 0.9167 |
| 0.2495 | 1.99 | 72 | 0.1087 | 0.9583 |
| 0.1026 | 2.98 | 108 | 0.0239 | 1.0 |
| 0.039 | 4.0 | 145 | 0.0605 | 0.9583 |
| 0.0188 | 4.99 | 181 | 0.1663 | 0.9375 |
| 0.0165 | 5.99 | 217 | 0.0047 | 1.0 |
| 0.0047 | 6.98 | 253 | 0.0028 | 1.0 |
| 0.005 | 8.0 | 290 | 0.0043 | 1.0 |
| 0.0022 | 8.99 | 326 | 0.0061 | 1.0 |
| 0.0015 | 9.93 | 360 | 0.0042 | 1.0 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for ahmedesmail16/Psoriasis-Project-Aug-M2-beit-base-patch16-224-pt22k-ft22k
Base model
microsoft/beit-base-patch16-224-pt22k-ft22k
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ahmedesmail16/Psoriasis-Project-Aug-M2-beit-base-patch16-224-pt22k-ft22k") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")