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README.md

@@ -1,10 +1,4 @@
-
-from pathlib import Path
-
-DATASET_ID = "cassieli226/2025-24679-image-dataset"  
-repo_dir = Path("autogluon_image_artifacts")         
-
-yaml_header = """---
+---
 tags:
 - autogluon
 - image
@@ -17,29 +11,22 @@ datasets:
 metrics:
 - accuracy
 - f1
----"""
+---
 
-body = f"""
 # HW2 — Image AutoML
 
-**Model**: timm/ResNet-18 via AutoGluon 1.4.0  
-**Task**: image classification
+## Description
+Trained with **AutoGluon** on an augmented image split (train/test) and validated on the original split. Backbone: `timm/resnet18`.
 
-## Results
-- Test (augmented): accuracy {acc_t:.4f}, F1-weighted {f1w_t:.4f}
-- External (original): accuracy {acc_o:.4f}, F1-weighted {f1w_o:.4f}
+- **Problem Type**: `image-classification`
+- **Preset**: `medium_quality`
 
 ## Data
-- Dataset: {DATASET_ID}
-- Splits: augmented → train/test, original → external validation
-
-## Training
-- preset: medium_quality
-- epochs: 6
-- batch size: 16
-- lr: 5e-4
-""".lstrip()
+- Train samples: 256
+- Test samples: 64
+- External (original) samples: 40
+- Dataset: `cassieli226/2025-24679-image-dataset`
 
-repo_dir.mkdir(parents=True, exist_ok=True)
-readme_path = repo_dir / "README.md"
-readme_path.write_text(yaml_header + "\n\n" + body, encoding="utf-8")
+## Results
+- **Test (accuracy / f1_weighted)**: 1.0000 / 1.0000
+- **Original (accuracy / f1_weighted)**: 1.0000 / 1.0000

predictor/assets.json

@@ -0,0 +1 @@
+{"learner_class": "BaseLearner", "column_types": {"image": "image_path", "label": "categorical"}, "label_column": "label", "problem_type": "binary", "presets": "medium_quality", "eval_metric_name": "accuracy", "validation_metric_name": "accuracy", "minmax_mode": "max", "output_shape": 2, "save_path": "/content/autogluon_image_artifacts/predictor", "pretrained": true, "pretrained_path": null, "fit_called": true, "best_score": null, "total_train_time": null, "version": "1.4.0"}

predictor/config.yaml

@@ -0,0 +1,142 @@
+model:
+  names:
+  - timm_image
+  timm_image:
+    checkpoint_name: resnet18
+    mix_choice: all_logits
+    data_types:
+    - image
+    train_transforms:
+    - resize_shorter_side
+    - center_crop
+    - trivial_augment
+    val_transforms:
+    - resize_shorter_side
+    - center_crop
+    image_norm: imagenet
+    image_size: null
+    image_chan_num: 3
+    use_learnable_image: false
+    max_image_num_per_column: 1
+data:
+  image:
+    missing_value_strategy: zero
+  text:
+    normalize_text: false
+  categorical:
+    minimum_cat_count: 100
+    maximum_num_cat: 20
+    convert_to_text: false
+    convert_to_text_template: latex
+  numerical:
+    convert_to_text: false
+    scaler_with_mean: true
+    scaler_with_std: true
+  document:
+    missing_value_strategy: zero
+  label:
+    numerical_preprocessing: standardscaler
+  pos_label: null
+  column_features_pooling_mode: concat
+  mixup:
+    turn_on: false
+    mixup_alpha: 0.8
+    cutmix_alpha: 1.0
+    cutmix_minmax: null
+    prob: 1.0
+    switch_prob: 0.5
+    mode: batch
+    turn_off_epoch: 5
+    label_smoothing: 0.1
+  modality_dropout: 0
+  templates:
+    turn_on: false
+    num_templates: 30
+    template_length: 2048
+    preset_templates:
+    - super_glue
+    - rte
+    custom_templates: null
+optim:
+  optim_type: adamw
+  lr: 0.0005
+  weight_decay: 0.001
+  lr_choice: layerwise_decay
+  lr_decay: 0.9
+  lr_schedule: cosine_decay
+  max_epochs: 6
+  max_steps: -1
+  warmup_steps: 0.1
+  end_lr: 0
+  lr_mult: 1
+  patience: 10
+  val_check_interval: 0.5
+  check_val_every_n_epoch: 1
+  skip_final_val: false
+  gradient_clip_val: 1
+  gradient_clip_algorithm: norm
+  track_grad_norm: -1
+  log_every_n_steps: 10
+  label_smoothing: 0
+  top_k: 3
+  top_k_average_method: greedy_soup
+  peft: null
+  lora:
+    module_filter: null
+    filter:
+    - query
+    - value
+    - ^q$
+    - ^v$
+    - ^k$
+    - ^o$
+    r: 8
+    alpha: 8
+    conv_lora_expert_num: 8
+  loss_func: auto
+  focal_loss:
+    alpha: null
+    gamma: 2.0
+    reduction: mean
+  mask2former_loss:
+    loss_cross_entropy_weight: 10.0
+    loss_mask_weight: 5.0
+    loss_dice_weight: 5.0
+  extra_trainable_params: []
+  cross_modal_align: null
+  cross_modal_align_weight: 0
+  automatic_optimization: true
+  lemda:
+    turn_on: false
+    arch_type: mlp_vae
+    z_dim: 8
+    num_layers: 6
+    kld_weight: 0.1
+    mse_weight: 0.1
+    adv_weight: 0.0001
+    consist_weight: 0.01
+    consist_threshold: 0.5
+    lr: 0.0001
+    optim_type: adamw
+    weight_decay: 1.0e-05
+env:
+  num_gpus: 0
+  num_nodes: 1
+  batch_size: 16
+  per_gpu_batch_size: 16
+  inference_batch_size_ratio: 4
+  precision: 32
+  num_workers: 0
+  num_workers_inference: 2
+  accelerator: auto
+  fast_dev_run: false
+  deterministic: false
+  auto_select_gpus: true
+  strategy: auto
+  deepspeed_allgather_size: 1000000000.0
+  deepspeed_allreduce_size: 1000000000.0
+  compile:
+    turn_on: false
+    mode: default
+    dynamic: true
+    backend: inductor

predictor/data_processors.pkl

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predictor/df_preprocessor.pkl

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predictor/eval_metric.pkl

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predictor/hparams.yaml

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+optim_type: adamw
+lr_choice: layerwise_decay
+lr_schedule: cosine_decay
+lr: 0.0005
+lr_decay: 0.9
+end_lr: 0
+lr_mult: 1
+weight_decay: 0.001
+warmup_steps: 0.1
+validation_metric_name: accuracy
+peft: null
+mixup_off_epoch: 5
+skip_final_val: false
+track_grad_norm: -1
+cross_modal_align: null
+cross_modal_align_weight: 0
+automatic_optimization: true
+accumulate_grad_batches: 1
+gradient_clip_val: 1
+gradient_clip_algorithm: norm
+use_aug_optim: false
+aug_lr: 0.0001
+aug_weight_decay: 1.0e-05
+aug_optim_type: adamw

predictor/model.ckpt

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