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README.md

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+# CS701 Course Project Dataset
+
+For task "ViT Model Adaptation"
+
+## Overview
+This is an anonymized image classification dataset containing 10,000 classes.
+
+## Dataset Statistics
+- **Number of classes**: 10,000
+- **Training samples**: 450,000 (45 per class, with labels)
+- **Validation samples**: 50,000 (5 per class, **without labels**)
+- **Test samples**: 100,000 (10 per class, **without labels**)
+
+## Dataset Structure
+```
+train/
+  class_0000/  # 45 images
+  class_0001/  # 45 images
+  ...
+  class_9999/  # 45 images
+
+val/
+  image_000000.jpg
+  image_000001.jpg
+  ...
+  image_049999.jpg
+
+test/
+  image_000000.jpg
+  image_000001.jpg
+  ...
+  image_099999.jpg
+```
+
+## Files
+- `train.txt`: Training image paths and labels (format: `train/class_XXXX/filename.jpg class_id`)
+- `val.txt`: Validation image paths only (format: `val/image_XXXXXX.jpg`)
+- `test.txt`: Test image paths only (format: `test/image_XXXXXX.jpg`)
+- `metadata.json`: Dataset metadata
+
+## Benchmark Submission
+
+1. Train your model on the training set (450,000 samples with labels)
+2. Generate predictions on validation set (50,000 samples without labels)
+3. Generate predictions on test set (100,000 samples without labels)
+4. Submit predictions to CodaBench for evaluation.
+
+### Prediction Format
+
+Your prediction files should follow this format:
+
+**val_predictions.txt**:
+```
+val/image_000000.jpg 1234
+val/image_000001.jpg 5678
+...
+val/image_049999.jpg 9012
+```
+
+**test_predictions.txt**:
+```
+test/image_000000.jpg 1234
+test/image_000001.jpg 5678
+...
+test/image_099999.jpg 9012
+```
+
+Each line contains: `<image_path> <predicted_class_id>` where class_id is in range [0, 9999].
+
+### Evaluation
+
+Submit your prediction files to the dataset maintainer for evaluation. The evaluation will compute:
+- Overall accuracy
+- Per-class accuracy
+- Additional metrics (if applicable)
+
+Note: Validation and test labels are withheld to prevent overfitting and ensure fair benchmarking.

metadata.json

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+{
+  "dataset_name": "cs701-course-data",
+  "description": "Anonymized image classification dataset with 10,000 classes",
+  "num_classes": 10000,
+  "train": {
+    "num_samples": 450000,
+    "samples_per_class": 45,
+    "label_available": true
+  },
+  "val": {
+    "num_samples": 50000,
+    "samples_per_class": 5,
+    "label_available": false,
+    "note": "Validation labels withheld for benchmark evaluation"
+  },
+  "test": {
+    "num_samples": 100000,
+    "samples_per_class": 10,
+    "label_available": false,
+    "note": "Test labels withheld for benchmark evaluation"
+  },
+  "image_format": "jpg",
+  "task": "ViT model adaptation"
+}