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README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: Indian-sign-language-classification
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# Indian-sign-language-classification
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.0327
+- Accuracy: 0.9905
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0003
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.01
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2504        | 1.0   | 2137 | 0.0731          | 0.9800   |
+| 0.0519        | 2.0   | 4274 | 0.0327          | 0.9905   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "google/vit-base-patch16-224-in21k",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "1",
+    "1": "2",
+    "10": "B",
+    "11": "C",
+    "12": "D",
+    "13": "E",
+    "14": "F",
+    "15": "G",
+    "16": "H",
+    "17": "I",
+    "18": "J",
+    "19": "K",
+    "2": "3",
+    "20": "L",
+    "21": "M",
+    "22": "N",
+    "23": "O",
+    "24": "P",
+    "25": "Q",
+    "26": "R",
+    "27": "S",
+    "28": "T",
+    "29": "U",
+    "3": "4",
+    "30": "V",
+    "31": "W",
+    "32": "X",
+    "33": "Y",
+    "34": "Z",
+    "4": "5",
+    "5": "6",
+    "6": "7",
+    "7": "8",
+    "8": "9",
+    "9": "A"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "1": "0",
+    "2": "1",
+    "3": "2",
+    "4": "3",
+    "5": "4",
+    "6": "5",
+    "7": "6",
+    "8": "7",
+    "9": "8",
+    "A": "9",
+    "B": "10",
+    "C": "11",
+    "D": "12",
+    "E": "13",
+    "F": "14",
+    "G": "15",
+    "H": "16",
+    "I": "17",
+    "J": "18",
+    "K": "19",
+    "L": "20",
+    "M": "21",
+    "N": "22",
+    "O": "23",
+    "P": "24",
+    "Q": "25",
+    "R": "26",
+    "S": "27",
+    "T": "28",
+    "U": "29",
+    "V": "30",
+    "W": "31",
+    "X": "32",
+    "Y": "33",
+    "Z": "34"
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.2"
+}

model.safetensors

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preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

training_args.bin

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