fanaf91318
commited on
Commit
·
fd150b7
1
Parent(s):
e5f0fc1
End of training
Browse files- README.md +64 -0
- config.json +180 -0
- preprocessor_config.json +36 -0
- tf_model.h5 +3 -0
README.md
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---
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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tags:
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- generated_from_keras_callback
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model-index:
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- name: fanaf91318/image-classifier-78-10-epoch-clean
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results: []
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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probably proofread and complete it, then remove this comment. -->
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# fanaf91318/image-classifier-78-10-epoch-clean
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 0.7377
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- Validation Loss: 1.1864
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- Train Accuracy: 0.7046
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- Epoch: 9
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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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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 59000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
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- training_precision: float32
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### Training results
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| Train Loss | Validation Loss | Train Accuracy | Epoch |
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|:----------:|:---------------:|:--------------:|:-----:|
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| 3.7894 | 3.2415 | 0.3476 | 0 |
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| 2.9188 | 2.5308 | 0.4824 | 1 |
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| 2.2939 | 2.0642 | 0.5501 | 2 |
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| 1.8570 | 1.7353 | 0.5962 | 3 |
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| 1.5300 | 1.5211 | 0.6369 | 4 |
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| 1.2610 | 1.4143 | 0.6612 | 5 |
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| 1.0738 | 1.2610 | 0.6965 | 6 |
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| 0.9197 | 1.2404 | 0.6897 | 7 |
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| 0.8280 | 1.2069 | 0.6985 | 8 |
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| 0.7377 | 1.1864 | 0.7046 | 9 |
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### Framework versions
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- Transformers 4.41.2
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- TensorFlow 2.15.0
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- Datasets 2.19.2
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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/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": "avtomobil aksessuarlari",
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"1": "avtomobil yuvishvositalari",
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"10": "elektr generatorlari",
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"11": "elektr pol yuvgich va elektr supurgi",
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"12": "elektrasboblar",
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"13": "epilyatorlar",
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"14": "fleshxotira",
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"15": "gadjetlar",
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"16": "havo tozalagichlar",
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"17": "hub elektr uzaytirgich",
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"18": "iplarni tozalash vositasi",
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"19": "isitgich",
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"2": "bosimli yuvish mashinalari",
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"20": "katta oshxona anjomlari",
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"21": "kichik uskunalar",
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"22": "kiryuvishmashinalari",
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"23": "klaviatura va sichqoncha",
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"24": "kompyuter aksessuarlari",
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"25": "kompyuter kalonkalari",
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"26": "konditsionerlar",
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"27": "massajorlar",
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"28": "monitorlar",
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"29": "monobloklar",
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"3": "bug' generatorlari",
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"30": "multistaylerlar",
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"31": "musiqiy markazlar",
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"32": "namlagichlar",
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"33": "noutbuk sumkalari",
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"34": "noutbuklar",
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"35": "o'rnatiladigan maishiy texnika",
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"36": "ofis monitorlari",
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"37": "ofis noutbuklari",
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"38": "ovqat pishirish uchun",
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"39": "planshetlar",
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"4": "bug' tizimlari",
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"40": "printerlar va ko'p funksiyali qurilmalar",
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"41": "qalamlar",
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"42": "radar detektorlar",
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"43": "relevastabilizatorlar",
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"44": "robot changyutgichlar",
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"45": "sboblar",
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"46": "simsiz asboblar",
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"47": "simsiz bug'mashinasi",
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"48": "simsiz changyutgich",
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"49": "simsiz kolonkalar",
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"5": "bug' tozalagichlari",
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"50": "smartfonlar",
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"51": "sochkesgich",
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"52": "sochqisqichlari",
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"53": "sochquritgichlari",
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"54": "sochtekislovchi dazmollar",
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"55": "soundbarlar",
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"56": "stol uchun idishlar",
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"57": "suv sovutgichilar",
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"58": "suvisitgichlar",
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"59": "tarozilar",
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"6": "changyutgichlar",
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"60": "tashqi qattiqdisklar",
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"61": "telefon aksessuarlari",
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"62": "telefonlar",
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"63": "televizor aksessuarlar",
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"64": "televizorlar",
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"65": "tikuvmashinalari",
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"66": "tishcho'tkalari",
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"67": "trimmerlar",
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"68": "tv va kinoga obuna",
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"69": "uykinoteatrlari",
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"7": "chimo'rgich",
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"70": "ventilyatorlar",
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"71": "vertikal bug'mashinasi",
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"72": "videoregistratorlar",
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"73": "wi-firouterlar",
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"74": "yandeks",
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"75": "yordamchi idishlar",
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"76": "yuqori bosimli yuvish aksessuarlari",
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"8": "dazmol",
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"9": "dispenserlar"
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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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"avtomobil aksessuarlari": "0",
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"avtomobil yuvishvositalari": "1",
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"bosimli yuvish mashinalari": "2",
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"bug' generatorlari": "3",
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"bug' tizimlari": "4",
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"bug' tozalagichlari": "5",
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"changyutgichlar": "6",
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"chimo'rgich": "7",
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"dazmol": "8",
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"dispenserlar": "9",
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"elektr generatorlari": "10",
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"elektr pol yuvgich va elektr supurgi": "11",
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"elektrasboblar": "12",
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"epilyatorlar": "13",
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"fleshxotira": "14",
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"gadjetlar": "15",
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"havo tozalagichlar": "16",
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"hub elektr uzaytirgich": "17",
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"iplarni tozalash vositasi": "18",
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"isitgich": "19",
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"katta oshxona anjomlari": "20",
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"kichik uskunalar": "21",
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"kiryuvishmashinalari": "22",
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"klaviatura va sichqoncha": "23",
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"kompyuter aksessuarlari": "24",
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"kompyuter kalonkalari": "25",
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"konditsionerlar": "26",
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"massajorlar": "27",
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"monitorlar": "28",
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"monobloklar": "29",
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"multistaylerlar": "30",
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"musiqiy markazlar": "31",
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"namlagichlar": "32",
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"noutbuk sumkalari": "33",
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"noutbuklar": "34",
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"o'rnatiladigan maishiy texnika": "35",
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"ofis monitorlari": "36",
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"ofis noutbuklari": "37",
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"ovqat pishirish uchun": "38",
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"planshetlar": "39",
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"printerlar va ko'p funksiyali qurilmalar": "40",
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"qalamlar": "41",
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"radar detektorlar": "42",
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"relevastabilizatorlar": "43",
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"robot changyutgichlar": "44",
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"sboblar": "45",
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"simsiz asboblar": "46",
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"simsiz bug'mashinasi": "47",
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"simsiz changyutgich": "48",
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"simsiz kolonkalar": "49",
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"smartfonlar": "50",
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"sochkesgich": "51",
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"sochqisqichlari": "52",
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"sochquritgichlari": "53",
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"sochtekislovchi dazmollar": "54",
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"soundbarlar": "55",
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"stol uchun idishlar": "56",
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"suv sovutgichilar": "57",
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"suvisitgichlar": "58",
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"tarozilar": "59",
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"tashqi qattiqdisklar": "60",
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"telefon aksessuarlari": "61",
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"telefonlar": "62",
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"televizor aksessuarlar": "63",
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"televizorlar": "64",
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"tikuvmashinalari": "65",
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"tishcho'tkalari": "66",
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"trimmerlar": "67",
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"tv va kinoga obuna": "68",
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"uykinoteatrlari": "69",
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"ventilyatorlar": "70",
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"vertikal bug'mashinasi": "71",
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"videoregistratorlar": "72",
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"wi-firouterlar": "73",
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"yandeks": "74",
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"yordamchi idishlar": "75",
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"yuqori bosimli yuvish aksessuarlari": "76"
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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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"qkv_bias": true,
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"transformers_version": "4.41.2"
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}
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preprocessor_config.json
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{
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"_valid_processor_keys": [
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"images",
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"do_resize",
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"size",
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"resample",
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"do_rescale",
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"rescale_factor",
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"do_normalize",
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"image_mean",
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"image_std",
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"return_tensors",
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"data_format",
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"input_data_format"
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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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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": "ViTImageProcessor",
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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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"height": 224,
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"width": 224
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}
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}
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:9249eafaca89b2d952e6b2c69866b27bd48071913418ae533135bef13fbbed3a
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size 343716536
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