Image Classification
Transformers
TensorBoard
Safetensors
mobilenet_v2
Generated from Trainer
Eval Results (legacy)
Instructions to use ozair23/mobilenet_v2_1.0_224-finetuned-plantdisease with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ozair23/mobilenet_v2_1.0_224-finetuned-plantdisease with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ozair23/mobilenet_v2_1.0_224-finetuned-plantdisease") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ozair23/mobilenet_v2_1.0_224-finetuned-plantdisease") model = AutoModelForImageClassification.from_pretrained("ozair23/mobilenet_v2_1.0_224-finetuned-plantdisease", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 0
Browse files
config.json
ADDED
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{
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"_name_or_path": "google/mobilenet_v2_1.0_224",
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"architectures": [
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"MobileNetV2ForImageClassification"
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],
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"classifier_dropout_prob": 0.2,
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"depth_divisible_by": 8,
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"depth_multiplier": 1.0,
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"expand_ratio": 6,
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"finegrained_output": true,
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"first_layer_is_expansion": true,
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"hidden_act": "relu6",
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"id2label": {
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"0": "Pepper__bell___Bacterial_spot",
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"1": "Pepper__bell___healthy",
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"2": "Potato___Early_blight",
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"3": "Potato___Late_blight",
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"4": "Potato___healthy",
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"5": "Tomato_Bacterial_spot",
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"6": "Tomato_Early_blight",
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"7": "Tomato_Late_blight",
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"8": "Tomato_Leaf_Mold",
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"9": "Tomato_Septoria_leaf_spot",
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"10": "Tomato_Spider_mites_Two_spotted_spider_mite",
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"11": "Tomato__Target_Spot",
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"12": "Tomato__Tomato_YellowLeaf__Curl_Virus",
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"13": "Tomato__Tomato_mosaic_virus",
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"14": "Tomato_healthy"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"label2id": {
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"Pepper__bell___Bacterial_spot": 0,
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"Pepper__bell___healthy": 1,
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"Potato___Early_blight": 2,
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"Potato___Late_blight": 3,
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"Potato___healthy": 4,
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"Tomato_Bacterial_spot": 5,
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"Tomato_Early_blight": 6,
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"Tomato_Late_blight": 7,
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"Tomato_Leaf_Mold": 8,
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"Tomato_Septoria_leaf_spot": 9,
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"Tomato_Spider_mites_Two_spotted_spider_mite": 10,
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"Tomato__Target_Spot": 11,
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"Tomato__Tomato_YellowLeaf__Curl_Virus": 12,
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"Tomato__Tomato_mosaic_virus": 13,
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"Tomato_healthy": 14
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},
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"layer_norm_eps": 0.001,
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"min_depth": 8,
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"model_type": "mobilenet_v2",
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"num_channels": 3,
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"output_stride": 32,
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"problem_type": "single_label_classification",
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"semantic_loss_ignore_index": 255,
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"tf_padding": true,
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"torch_dtype": "float32",
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"transformers_version": "4.44.2"
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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 sha256:941cc4f8631c592192a33858cc3d2d98df63d3aef8eeb7a3159364074a78b3a2
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size 9146828
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preprocessor_config.json
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{
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"crop_size": {
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"height": 224,
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"width": 224
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},
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"do_center_crop": true,
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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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0.5,
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0.5,
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0.5
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],
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"image_processor_type": "MobileNetV2FeatureExtractor",
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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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"rescale_factor": 0.00392156862745098,
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"size": {
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"shortest_edge": 256
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}
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}
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runs/Nov09_07-39-40_1bdfc3ee065a/events.out.tfevents.1731138011.1bdfc3ee065a.277.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:0e898f7b0973c4546078b0890c1f08f8b1529d720ed068b855e98488f429c612
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size 9306
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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:a8dd73be935d75ab62152e515cfe509bbfaf6b61c48c5efc6df85e56f7ec5c07
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size 5240
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