ViTAMIn-O Auto-Upload: Seed 42

README.md

@@ -1,3 +1,28 @@
----
-license: mit
----
+---
+tags:
+- image-classification
+- biology
+- organoids
+- vitamin-o
+library_name: transformers
+---
+
+# ViTAMIn-O Custom Organoid Model
+
+This model was trained using the **ColabViTAMIn-O** code-free infrastructure.
+
+## Model Details
+* **Base Architecture:** `ViTAMIn-O/ViTAMIn-O_base_model`
+* **Task Type:** `Classification`
+* **Repository:** `ViTAMIn-O/PDLO_classifier`
+
+## Training Hyperparameters
+* **Seed:** `42`
+* **Epochs:** `20`
+* **Batch Size:** `32`
+
+## Evaluation Metrics (Test Set)
+* **Accuracy:** `0.9250`
+* **Global AUROC:** `0.9881`
+
+*This model card was auto-generated by the ViTAMIn-O pipeline to ensure reproducibility and open-science transparency.*

best_metric_tracker.json

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+{"best_auroc": 0.988125, "seed": 42}

config.json

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+{
+  "architectures": [
+    "SwinForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "depths": [
+    2,
+    2,
+    18,
+    2
+  ],
+  "drop_path_rate": 0.1,
+  "dtype": "float32",
+  "embed_dim": 192,
+  "encoder_stride": 32,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 1536,
+  "id2label": {
+    "0": "satisfactory",
+    "1": "unsatisfactory"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "satisfactory": 0,
+    "unsatisfactory": 1
+  },
+  "layer_norm_eps": 1e-05,
+  "mlp_ratio": 4.0,
+  "model_type": "swin",
+  "num_channels": 3,
+  "num_heads": [
+    6,
+    12,
+    24,
+    48
+  ],
+  "num_layers": 4,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "patch_size": 4,
+  "path_norm": true,
+  "qkv_bias": true,
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "5.0.0",
+  "use_absolute_embeddings": false,
+  "window_size": 7
+}

history_seed_42.csv

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model.safetensors

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+oid sha256:9edd84bb8d05044392bd402b8c1b4ea2c5bd82ef5c446cce46db4fcb63e1a615
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predictions_seed_42.csv

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preprocessor_config.json

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+{
+  "data_format": "channels_first",
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
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+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTImageProcessorFast",
+  "image_std": [
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+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

results_seed_42.json

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+{"Accuracy": 0.925, "Balanced_Accuracy": 0.925, "MCC": 0.8510644963469901, "Cohen_Kappa": 0.85, "Brier_Score": 0.04958225747752335, "Global_AUROC": 0.988125, "satisfactory_AUROC": 0.988125, "unsatisfactory_AUROC": 0.988125, "satisfactory_Precision": 0.9047619047619048, "satisfactory_Recall": 0.95, "satisfactory_Specificity": 0.9, "satisfactory_NPV": 0.9473684210526315, "satisfactory_F1": 0.9268292682926829, "unsatisfactory_Precision": 0.9473684210526315, "unsatisfactory_Recall": 0.9, "unsatisfactory_Specificity": 0.95, "unsatisfactory_NPV": 0.9047619047619048, "unsatisfactory_F1": 0.9230769230769231, "Macro_Precision": 0.9260651629072681, "Macro_Recall": 0.925, "Macro_Specificity": 0.925, "Macro_F1": 0.924953095684803, "Seed": 42}