End of training
Browse files- README.md +62 -0
- config.json +101 -0
- model.safetensors +3 -0
- preprocessor_config.json +29 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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base_model: google/efficientnet-b0
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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model-index:
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- name: SkinCancerClassifier_Plain-V1
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jhoppanne-myself/finalProject/runs/ow4dk70u)
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jhoppanne-myself/finalProject/runs/ow4dk70u)
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jhoppanne-myself/finalProject/runs/ow4dk70u)
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jhoppanne-myself/finalProject/runs/8hxuz0bh)
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# SkinCancerClassifier_Plain-V1
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This model is a fine-tuned version of [google/efficientnet-b0](https://huggingface.co/google/efficientnet-b0) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 1.0790
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- eval_accuracy: 0.7792
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- eval_runtime: 1.5074
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- eval_samples_per_second: 159.219
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- eval_steps_per_second: 5.307
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- epoch: 104.5667
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- step: 3137
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-06
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 2000
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### Framework versions
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- Transformers 4.42.2
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- Pytorch 2.3.0
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- Datasets 2.15.0
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "google/efficientnet-b0",
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"architectures": [
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"EfficientNetForImageClassification"
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],
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"batch_norm_eps": 0.001,
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"batch_norm_momentum": 0.99,
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"depth_coefficient": 1.0,
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"depth_divisor": 8,
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"depthwise_padding": [],
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"drop_connect_rate": 0.2,
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"dropout_rate": 0.2,
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"expand_ratios": [
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1,
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6,
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6,
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6,
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6,
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6,
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6
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],
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"hidden_act": "swish",
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"hidden_dim": 1280,
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"id2label": {
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"0": "Benign",
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"1": "Indeterminate",
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"2": "Malignant"
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},
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"image_size": 224,
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"in_channels": [
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32,
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16,
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24,
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40,
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80,
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112,
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192
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],
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"initializer_range": 0.02,
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"kernel_sizes": [
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3,
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3,
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5,
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],
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"label2id": {
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"Benign": "0",
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"Indeterminate": "1",
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"Malignant": "2"
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},
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"model_type": "efficientnet",
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"num_block_repeats": [
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1,
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],
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"num_channels": 3,
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"num_hidden_layers": 64,
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"out_channels": [
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16,
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24,
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40,
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80,
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112,
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192,
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320
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],
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"out_features": null,
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"pooling_type": "mean",
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"problem_type": "single_label_classification",
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"squeeze_expansion_ratio": 0.25,
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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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"stage5",
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"stage6",
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"stage7"
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],
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"strides": [
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1,
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1
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],
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"torch_dtype": "float32",
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"transformers_version": "4.42.2",
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"width_coefficient": 1.0
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ed99914513ef367aeb5f5a698bef3a66dcba7bce2d0f8dae38819463632e654c
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size 16260252
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preprocessor_config.json
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{
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"crop_size": {
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"height": 289,
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"width": 289
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},
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"do_center_crop": false,
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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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0.485,
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0.456,
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0.406
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],
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"image_processor_type": "EfficientNetImageProcessor",
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"image_std": [
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0.47853944,
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0.4732864,
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0.47434163
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],
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"include_top": true,
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"resample": 0,
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"rescale_factor": 0.00392156862745098,
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"rescale_offset": false,
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"size": {
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"height": 224,
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"width": 224
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}
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:a43d2c85e2467e2ba03a93f36f7bc5bdae1da1b72049c8129174faa4377995a8
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size 5176
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