End of training

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: ViT_MNIST
+  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. -->
+
+# ViT_MNIST
+
+This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2367
+- Accuracy: 0.9379
+
+## 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: 5e-05
+- train_batch_size: 5500
+- eval_batch_size: 5500
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3795        | 1.0   | 11   | 0.3894          | 0.897    |
+| 0.3668        | 2.0   | 22   | 0.3547          | 0.9059   |
+| 0.3441        | 3.0   | 33   | 0.3186          | 0.9174   |
+| 0.3163        | 4.0   | 44   | 0.2998          | 0.9235   |
+| 0.299         | 5.0   | 55   | 0.2860          | 0.9259   |
+| 0.2788        | 6.0   | 66   | 0.2770          | 0.9291   |
+| 0.2684        | 7.0   | 77   | 0.2553          | 0.9342   |
+| 0.2579        | 8.0   | 88   | 0.2545          | 0.9338   |
+| 0.2449        | 9.0   | 99   | 0.2403          | 0.9378   |
+| 0.2322        | 10.0  | 110  | 0.2367          | 0.9379   |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

config.json

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+{
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 256,
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "image_size": 28,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "0": "0",
+    "1": "1",
+    "2": "2",
+    "3": "3",
+    "4": "4",
+    "5": "5",
+    "6": "6",
+    "7": "7",
+    "8": "8",
+    "9": "9"
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 8,
+  "num_channels": 1,
+  "num_hidden_layers": 3,
+  "patch_size": 7,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.42.4"
+}

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": 28,
+    "width": 28
+  }
+}

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