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google-vit-base-patch16-384-in21k-batch_16_epoch_4_classes_24_final_withAug_12th_May

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  1. README.md +121 -0
  2. config.json +76 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +36 -0
  5. runs/May11_19-53-00_9479ebf6a298/events.out.tfevents.1715457189.9479ebf6a298.34.0 +3 -0
  6. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/vit-base-patch16-384
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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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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: google-vit-base-patch16-384-in21k-batch_16_epoch_4_classes_24_final_withAug_12th_May
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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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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9904891304347826
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+ ---
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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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+
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+ # google-vit-base-patch16-384-in21k-batch_16_epoch_4_classes_24_final_withAug_12th_May
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0282
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+ - Accuracy: 0.9905
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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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: 4
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.269 | 0.09 | 100 | 0.4001 | 0.8723 |
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+ | 0.1829 | 0.17 | 200 | 0.0928 | 0.9728 |
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+ | 0.1737 | 0.26 | 300 | 0.1615 | 0.9457 |
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+ | 0.2096 | 0.34 | 400 | 0.4138 | 0.9022 |
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+ | 0.1855 | 0.43 | 500 | 0.1814 | 0.9511 |
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+ | 0.0901 | 0.51 | 600 | 0.1435 | 0.9579 |
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+ | 0.1406 | 0.6 | 700 | 0.1468 | 0.9620 |
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+ | 0.136 | 0.68 | 800 | 0.1532 | 0.9565 |
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+ | 0.0666 | 0.77 | 900 | 0.1177 | 0.9674 |
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+ | 0.1145 | 0.85 | 1000 | 0.1794 | 0.9497 |
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+ | 0.0865 | 0.94 | 1100 | 0.1113 | 0.9688 |
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+ | 0.0612 | 1.02 | 1200 | 0.1270 | 0.9688 |
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+ | 0.0038 | 1.11 | 1300 | 0.0724 | 0.9783 |
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+ | 0.0006 | 1.19 | 1400 | 0.0715 | 0.9851 |
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+ | 0.0007 | 1.28 | 1500 | 0.0616 | 0.9796 |
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+ | 0.0579 | 1.36 | 1600 | 0.1259 | 0.9715 |
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+ | 0.0009 | 1.45 | 1700 | 0.1028 | 0.9755 |
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+ | 0.0295 | 1.53 | 1800 | 0.0637 | 0.9823 |
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+ | 0.0484 | 1.62 | 1900 | 0.0893 | 0.9783 |
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+ | 0.0371 | 1.71 | 2000 | 0.0637 | 0.9837 |
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+ | 0.0359 | 1.79 | 2100 | 0.0389 | 0.9878 |
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+ | 0.0006 | 1.88 | 2200 | 0.0750 | 0.9823 |
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+ | 0.0189 | 1.96 | 2300 | 0.0451 | 0.9851 |
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+ | 0.0442 | 2.05 | 2400 | 0.0772 | 0.9796 |
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+ | 0.0006 | 2.13 | 2500 | 0.1988 | 0.9620 |
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+ | 0.006 | 2.22 | 2600 | 0.0659 | 0.9864 |
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+ | 0.0093 | 2.3 | 2700 | 0.0754 | 0.9810 |
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+ | 0.0008 | 2.39 | 2800 | 0.0800 | 0.9783 |
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+ | 0.0003 | 2.47 | 2900 | 0.0617 | 0.9864 |
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+ | 0.0094 | 2.56 | 3000 | 0.0736 | 0.9837 |
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+ | 0.0001 | 2.64 | 3100 | 0.0538 | 0.9823 |
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+ | 0.001 | 2.73 | 3200 | 0.0606 | 0.9878 |
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+ | 0.0001 | 2.81 | 3300 | 0.0433 | 0.9864 |
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+ | 0.0001 | 2.9 | 3400 | 0.0583 | 0.9823 |
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+ | 0.0001 | 2.98 | 3500 | 0.0388 | 0.9905 |
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+ | 0.0001 | 3.07 | 3600 | 0.0408 | 0.9891 |
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+ | 0.0001 | 3.15 | 3700 | 0.0375 | 0.9891 |
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+ | 0.0001 | 3.24 | 3800 | 0.0367 | 0.9878 |
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+ | 0.0001 | 3.32 | 3900 | 0.0355 | 0.9878 |
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+ | 0.0001 | 3.41 | 4000 | 0.0395 | 0.9878 |
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+ | 0.0001 | 3.5 | 4100 | 0.0382 | 0.9878 |
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+ | 0.0001 | 3.58 | 4200 | 0.0399 | 0.9891 |
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+ | 0.0001 | 3.67 | 4300 | 0.0396 | 0.9891 |
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+ | 0.0072 | 3.75 | 4400 | 0.0355 | 0.9905 |
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+ | 0.0001 | 3.84 | 4500 | 0.0284 | 0.9918 |
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+ | 0.0001 | 3.92 | 4600 | 0.0282 | 0.9905 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
config.json ADDED
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+ {
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+ "_name_or_path": "google/vit-base-patch16-384",
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+ "architectures": [
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+ "ViTForImageClassification"
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+ "id2label": {
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+ "0": "Bhapa Pitha(\u09ad\u09be\u09aa\u09be \u09aa\u09bf\u09a0\u09be)",
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+ "1": "Biriyani(\u09ac\u09bf\u09b0\u09bf\u09df\u09be\u09a8\u09bf)",
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+ "10": "Khichuri(\u0996\u09bf\u099a\u09c1\u09a1\u09bc\u09bf)",
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+ "11": "Malpua Pitha(\u09ae\u09be\u09b2\u09aa\u09c1\u09df\u09be \u09aa\u09bf\u09a0\u09be)",
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+ "12": "Mustard Hilsa(\u09b8\u09b0\u09b7\u09c7 \u0987\u09b2\u09bf\u09b6)",
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+ "13": "Nakshi Pitha(\u09a8\u0995\u09b6\u09bf \u09aa\u09bf\u09a0\u09be)",
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+ "14": "Panta Ilish(\u09aa\u09be\u09a8\u09cd\u09a4\u09be \u0987\u09b2\u09bf\u09b6)",
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+ "15": "Patishapta Pitha(\u09aa\u09be\u099f\u09bf\u09b8\u09be\u09aa\u099f\u09be)",
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+ "16": "Prawn Malai Curry(\u099a\u09bf\u0982\u09dc\u09bf \u09ae\u09be\u09b2\u09be\u0987\u0995\u09be\u09b0\u09c0)",
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+ "17": "Rasgulla(\u09b0\u09b8\u0997\u09cb\u09b2\u09cd\u09b2\u09be)",
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+ "18": "Rose Cookies(\u09ab\u09c1\u09b2\u099d\u09c1\u09b0\u09bf \u09aa\u09bf\u09a0\u09be)",
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+ "19": "Roshmalai(\u09b0\u09b8\u09ae\u09be\u09b2\u09be\u0987)",
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+ "2": "Chicken Pulao(\u09ae\u09cb\u09b0\u0997 \u09aa\u09cb\u09b2\u09be\u0993)",
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+ "20": "Shahi Tukra(\u09b6\u09be\u09b9\u09bf \u099f\u09c1\u0995\u09b0\u09be)",
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+ "21": "Shingara(\u09b8\u09bf\u0999\u09cd\u0997\u09be\u09b0\u09be)",
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+ "22": "Sweet Yogurt(\u09ae\u09bf\u09b7\u09cd\u099f\u09bf \u09a6\u0987)",
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+ "23": "Tehari(\u09a4\u09c7\u09b9\u09be\u09b0\u09bf)",
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+ "3": "Chickpease Bhuna(\u099b\u09cb\u09b2\u09be\u09ad\u09c1\u09a8\u09be)",
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+ "4": "Egg Curry(\u09a1\u09bf\u09ae\u09ad\u09c1\u09a8\u09be)",
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+ "5": "Falooda(\u09ab\u09be\u09b2\u09c1\u09a6\u09be)",
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+ "6": "Fuchka(\u09ab\u09c1\u099a\u0995\u09be)",
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+ "7": "Haleem(\u09b9\u09be\u09b2\u09bf\u09ae)",
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+ "8": "Jalebi(\u099c\u09bf\u09b2\u09be\u09aa\u09c0)",
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+ "9": "Kala Bhuna(\u0995\u09be\u09b2\u09be \u09ad\u09c1\u09a8\u09be)"
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+ },
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+ "image_size": 384,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "Bhapa Pitha(\u09ad\u09be\u09aa\u09be \u09aa\u09bf\u09a0\u09be)": "0",
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+ "Biriyani(\u09ac\u09bf\u09b0\u09bf\u09df\u09be\u09a8\u09bf)": "1",
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+ "Chicken Pulao(\u09ae\u09cb\u09b0\u0997 \u09aa\u09cb\u09b2\u09be\u0993)": "2",
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+ "Chickpease Bhuna(\u099b\u09cb\u09b2\u09be\u09ad\u09c1\u09a8\u09be)": "3",
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+ "Egg Curry(\u09a1\u09bf\u09ae\u09ad\u09c1\u09a8\u09be)": "4",
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+ "Falooda(\u09ab\u09be\u09b2\u09c1\u09a6\u09be)": "5",
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+ "Kala Bhuna(\u0995\u09be\u09b2\u09be \u09ad\u09c1\u09a8\u09be)": "9",
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+ "Khichuri(\u0996\u09bf\u099a\u09c1\u09a1\u09bc\u09bf)": "10",
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+ "Malpua Pitha(\u09ae\u09be\u09b2\u09aa\u09c1\u09df\u09be \u09aa\u09bf\u09a0\u09be)": "11",
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+ "Mustard Hilsa(\u09b8\u09b0\u09b7\u09c7 \u0987\u09b2\u09bf\u09b6)": "12",
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+ "Nakshi Pitha(\u09a8\u0995\u09b6\u09bf \u09aa\u09bf\u09a0\u09be)": "13",
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+ "Panta Ilish(\u09aa\u09be\u09a8\u09cd\u09a4\u09be \u0987\u09b2\u09bf\u09b6)": "14",
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+ "Patishapta Pitha(\u09aa\u09be\u099f\u09bf\u09b8\u09be\u09aa\u099f\u09be)": "15",
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+ "Prawn Malai Curry(\u099a\u09bf\u0982\u09dc\u09bf \u09ae\u09be\u09b2\u09be\u0987\u0995\u09be\u09b0\u09c0)": "16",
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+ "Rasgulla(\u09b0\u09b8\u0997\u09cb\u09b2\u09cd\u09b2\u09be)": "17",
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+ "Rose Cookies(\u09ab\u09c1\u09b2\u099d\u09c1\u09b0\u09bf \u09aa\u09bf\u09a0\u09be)": "18",
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+ "Roshmalai(\u09b0\u09b8\u09ae\u09be\u09b2\u09be\u0987)": "19",
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+ "Shahi Tukra(\u09b6\u09be\u09b9\u09bf \u099f\u09c1\u0995\u09b0\u09be)": "20",
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+ "Shingara(\u09b8\u09bf\u0999\u09cd\u0997\u09be\u09b0\u09be)": "21",
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+ "Sweet Yogurt(\u09ae\u09bf\u09b7\u09cd\u099f\u09bf \u09a6\u0987)": "22",
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+ "Tehari(\u09a4\u09c7\u09b9\u09be\u09b0\u09bf)": "23"
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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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+ "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": "4.39.3"
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