Autogluon trained ML classifier
Browse files- assets.json +1 -0
- config.yaml +122 -0
- data_processors.pkl +3 -0
- df_preprocessor.pkl +3 -0
- hparams.yaml +15 -0
- model.ckpt +3 -0
assets.json
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{"class_name": "BaseLearner", "column_types": {"image": "image_path", "label": "categorical"}, "label_column": "label", "problem_type": "multiclass", "presets": null, "eval_metric_name": "accuracy", "validation_metric_name": "accuracy", "minmax_mode": "max", "output_shape": 3, "save_path": "./tmp/2f5bfeedd28a488d8f940e6568bea15b-beeml", "pretrained": true, "pretrained_path": null, "fit_called": true, "best_score": 0.9559999704360962, "total_train_time": 18989.389338970184, "version": "1.1.1"}
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config.yaml
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model:
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names:
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- timm_image
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timm_image:
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checkpoint_name: caformer_b36.sail_in22k_ft_in1k
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mix_choice: all_logits
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data_types:
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- image
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train_transforms:
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- resize_shorter_side
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- center_crop
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- trivial_augment
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val_transforms:
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- resize_shorter_side
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- center_crop
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image_norm: imagenet
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image_size: null
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max_img_num_per_col: 2
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data:
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image:
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missing_value_strategy: zero
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text:
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normalize_text: false
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categorical:
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minimum_cat_count: 100
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maximum_num_cat: 20
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convert_to_text: false
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numerical:
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convert_to_text: false
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scaler_with_mean: true
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scaler_with_std: true
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document:
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missing_value_strategy: zero
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label:
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numerical_label_preprocessing: standardscaler
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pos_label: null
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column_features_pooling_mode: concat
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mixup:
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turn_on: false
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mixup_alpha: 0.8
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cutmix_alpha: 1.0
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cutmix_minmax: null
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prob: 1.0
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switch_prob: 0.5
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mode: batch
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turn_off_epoch: 5
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label_smoothing: 0.1
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templates:
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turn_on: false
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num_templates: 30
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template_length: 2048
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preset_templates:
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- super_glue
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- rte
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custom_templates: null
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optimization:
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optim_type: adamw
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learning_rate: 0.0001
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weight_decay: 0.001
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lr_choice: layerwise_decay
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lr_decay: 0.9
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lr_schedule: cosine_decay
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max_epochs: 20
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max_steps: -1
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warmup_steps: 0.1
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end_lr: 0
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lr_mult: 1
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patience: 10
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val_check_interval: 0.5
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check_val_every_n_epoch: 1
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skip_final_val: false
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gradient_clip_val: 1
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gradient_clip_algorithm: norm
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track_grad_norm: -1
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log_every_n_steps: 10
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top_k: 3
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top_k_average_method: greedy_soup
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efficient_finetune: null
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lora:
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module_filter: null
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filter:
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- query
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- value
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- ^q$
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- ^v$
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- ^k$
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- ^o$
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r: 8
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alpha: 8
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conv_lora_expert_num: 8
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loss_function: auto
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focal_loss:
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alpha: null
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gamma: 2.0
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reduction: mean
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mask2former_loss:
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loss_cross_entropy_weight: 10.0
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loss_mask_weight: 5.0
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loss_dice_weight: 5.0
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extra_trainable_params: []
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env:
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num_gpus: 0
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num_nodes: 1
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batch_size: 128
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per_gpu_batch_size: 8
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eval_batch_size_ratio: 4
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per_gpu_batch_size_evaluation: null
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precision: 32
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num_workers: 2
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num_workers_evaluation: 2
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accelerator: auto
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fast_dev_run: false
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deterministic: false
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auto_select_gpus: true
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strategy: auto
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deepspeed_allgather_size: 1000000000.0
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deepspeed_allreduce_size: 1000000000.0
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compile:
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turn_on: false
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mode: default
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dynamic: true
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backend: inductor
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data_processors.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:ac50b1c3eb0c55a9edb546f395dde19a59aa8997e2d8d0c6754ac6e78dabc7dc
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size 1527
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df_preprocessor.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:b4fa4cee62873fa91e25f9344ea640c4f8d1a06319968984a890a25551a6f650
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size 11769
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hparams.yaml
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optim_type: adamw
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lr_choice: layerwise_decay
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lr_schedule: cosine_decay
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lr: 0.0001
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lr_decay: 0.9
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end_lr: 0
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lr_mult: 1
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weight_decay: 0.001
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warmup_steps: 0.1
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validation_metric_name: accuracy
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custom_metric_func: null
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efficient_finetune: null
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mixup_off_epoch: 5
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skip_final_val: false
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track_grad_norm: -1
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model.ckpt
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version https://git-lfs.github.com/spec/v1
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oid sha256:cbf8b492411b79c41b3cb72df933b340bbe94fe028187b5c99a3c8a654d64e6e
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size 382867646
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