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Browse files- README.md +31 -0
- checkpoint-528/config.json +50 -0
- checkpoint-528/model.safetensors +3 -0
- checkpoint-528/optimizer.pt +3 -0
- checkpoint-528/rng_state.pth +3 -0
- checkpoint-528/scheduler.pt +3 -0
- checkpoint-528/trainer_state.json +0 -0
- checkpoint-528/training_args.bin +3 -0
- config.json +50 -0
- model.safetensors +3 -0
- preprocessor_config.json +22 -0
- runs/Aug17_22-41-21_tufta/events.out.tfevents.1723948881.tufta.66785.0 +2 -2
- runs/Aug17_22-41-21_tufta/events.out.tfevents.1723949877.tufta.66785.1 +3 -0
- training_args.bin +3 -0
- training_params.json +29 -0
README.md
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---
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tags:
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- autotrain
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- image-classification
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base_model: microsoft/resnet-152
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widget:
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
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example_title: Tiger
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
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example_title: Teapot
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg
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example_title: Palace
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---
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# Model Trained Using AutoTrain
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- Problem type: Image Classification
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## Validation Metrics
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loss: 0.2574561536312103
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f1: 0.8857142857142857
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precision: 0.8611111111111112
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recall: 0.9117647058823529
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auc: 0.9705882352941176
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accuracy: 0.8709677419354839
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checkpoint-528/config.json
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{
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"_name_or_path": "microsoft/resnet-152",
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"_num_labels": 2,
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"architectures": [
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"ResNetForImageClassification"
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],
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"depths": [
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3,
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36,
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],
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"downsample_in_bottleneck": false,
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"downsample_in_first_stage": false,
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"embedding_size": 64,
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"hidden_act": "relu",
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"hidden_sizes": [
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256,
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512,
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1024,
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2048
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],
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"id2label": {
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"0": "no",
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"1": "yes"
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},
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"label2id": {
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"no": 0,
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"yes": 1
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},
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"layer_type": "bottleneck",
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"model_type": "resnet",
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"num_channels": 3,
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"out_features": [
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"stage4"
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],
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"out_indices": [
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4
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],
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"problem_type": "single_label_classification",
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"stage_names": [
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"stem",
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"stage1",
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"stage2",
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"stage3",
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"stage4"
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],
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"torch_dtype": "float32",
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"transformers_version": "4.44.0"
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}
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checkpoint-528/model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 233321808
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checkpoint-528/optimizer.pt
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version https://git-lfs.github.com/spec/v1
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size 465576843
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checkpoint-528/rng_state.pth
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version https://git-lfs.github.com/spec/v1
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checkpoint-528/scheduler.pt
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checkpoint-528/trainer_state.json
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checkpoint-528/training_args.bin
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version https://git-lfs.github.com/spec/v1
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config.json
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{
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"_name_or_path": "microsoft/resnet-152",
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"_num_labels": 2,
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"architectures": [
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"ResNetForImageClassification"
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],
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"depths": [
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"downsample_in_bottleneck": false,
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"downsample_in_first_stage": false,
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"embedding_size": 64,
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"hidden_act": "relu",
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"hidden_sizes": [
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256,
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512,
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1024,
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2048
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"id2label": {
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"0": "no",
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"1": "yes"
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"label2id": {
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"no": 0,
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"yes": 1
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},
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"layer_type": "bottleneck",
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"model_type": "resnet",
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"num_channels": 3,
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"out_features": [
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"stage4"
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],
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"out_indices": [
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],
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"problem_type": "single_label_classification",
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"stage_names": [
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"stem",
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"stage1",
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"stage2",
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"stage3",
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"stage4"
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],
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"torch_dtype": "float32",
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"transformers_version": "4.44.0"
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}
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model.safetensors
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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],
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"image_processor_type": "ConvNextImageProcessor",
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"image_std": [
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0.229,
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0.224,
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0.225
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],
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"resample": 3,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"shortest_edge": 224
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}
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}
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runs/Aug17_22-41-21_tufta/events.out.tfevents.1723948881.tufta.66785.0
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runs/Aug17_22-41-21_tufta/events.out.tfevents.1723949877.tufta.66785.1
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training_args.bin
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training_params.json
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{
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"data_path": "prostate-mri-T2w-v03/autotrain-data",
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"model": "microsoft/resnet-152",
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"username": "Emilio407",
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"lr": 5e-05,
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"epochs": 50,
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"batch_size": 16,
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"warmup_ratio": 0.1,
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"gradient_accumulation": 1,
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"optimizer": "adamw_torch",
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"scheduler": "linear",
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"weight_decay": 0.0,
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"max_grad_norm": 1.0,
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"seed": 42,
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"train_split": "train",
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"valid_split": "validation",
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"logging_steps": -1,
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"project_name": "prostate-mri-T2w-v03",
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"auto_find_batch_size": false,
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"mixed_precision": "bf16",
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"save_total_limit": 1,
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"push_to_hub": true,
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"eval_strategy": "epoch",
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"image_column": "autotrain_image",
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"target_column": "autotrain_label",
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"log": "tensorboard",
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"early_stopping_patience": 15,
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"early_stopping_threshold": 0.01
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}
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