commit files to HF hub
Browse files- README.md +36 -0
- config.json +32 -0
- images/abnormal.tif +0 -0
- images/normal.tif +0 -0
- preprocessor_config.json +17 -0
- pytorch_model.bin +3 -0
- runs/events.out.tfevents.1650163859.cfec3453ec31.73.0 +3 -0
README.md
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---
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tags:
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- image-classification
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- pytorch
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- huggingpics
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metrics:
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- accuracy
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model-index:
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- name: anomaly
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results:
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- task:
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name: Image Classification
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type: image-classification
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metrics:
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- name: Accuracy
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type: accuracy
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value: 1.0
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---
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# anomaly
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Annomly classification
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## Example Images
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#### abnormal
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![abnormal](images/abnormal.tif)
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#### normal
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![normal](images/normal.tif)
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config.json
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{
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"_name_or_path": "google/vit-base-patch16-224-in21k",
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"architectures": [
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"ViTForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"encoder_stride": 16,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_size": 768,
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"id2label": {
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"0": "abnormal",
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"1": "normal"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"abnormal": "0",
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"normal": "1"
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},
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"layer_norm_eps": 1e-12,
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"model_type": "vit",
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"num_attention_heads": 12,
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"num_channels": 3,
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"num_hidden_layers": 12,
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"patch_size": 16,
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.18.0"
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}
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images/abnormal.tif
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images/normal.tif
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_resize": true,
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"feature_extractor_type": "ViTFeatureExtractor",
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"image_mean": [
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0.5,
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0.5,
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0.5
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],
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"image_std": [
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0.5,
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0.5,
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0.5
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],
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"resample": 2,
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"size": 224
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:bc785ee2c4d6fb9b9d1ccf15a8cd85d22ef55d3c2c76c183b1479c21683236f6
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size 343264177
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runs/events.out.tfevents.1650163859.cfec3453ec31.73.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:4d3eb22f940502c881a616dbb9914abc25ac66bbc67d5380f52a9b735de3db05
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size 972
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