rocky93/BraTS_segmentation
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How to use shumailabatool/brain_tumor_detection with Keras:
# Available backend options are: "jax", "torch", "tensorflow".
import os
os.environ["KERAS_BACKEND"] = "jax"
import keras
model = keras.saving.load_model("hf://shumailabatool/brain_tumor_detection")
This model is a fine-tuned version on the braTS20 dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3208 | 1 | 355 | 0.3162 | 0.9461 |
| 0.0392 | 2 | 268 | 0.1177 | 0.9893 |
| 0.0326 | 3 | 267 | 0.2596 | 0.9899 |
| 0.0351 | 4 | 267 | 0.3398 | 0.9888 |
| 0.0272 | 5 | 266 | 0.2636 | 0.9912 |