Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/vit-base-patch16-224
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: vit-finetuned-1
+  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-finetuned-1
+
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0605
+- Accuracy: 1.0
+
+## 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: 0.0002
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.3444        | 1.0   | 1    | 0.4903          | 0.6667   |
+| 0.1092        | 2.0   | 2    | 0.0592          | 1.0      |
+| 0.0094        | 3.0   | 3    | 0.0310          | 1.0      |
+| 0.0021        | 4.0   | 4    | 0.0303          | 1.0      |
+| 0.0008        | 5.0   | 5    | 0.0363          | 1.0      |
+| 0.0004        | 6.0   | 6    | 0.0442          | 1.0      |
+| 0.0003        | 7.0   | 7    | 0.0512          | 1.0      |
+| 0.0002        | 8.0   | 8    | 0.0567          | 1.0      |
+| 0.0002        | 9.0   | 9    | 0.0595          | 1.0      |
+| 0.0002        | 10.0  | 10   | 0.0605          | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.46.1
+- Pytorch 2.5.1+cpu
+- Datasets 3.1.0
+- Tokenizers 0.20.1

config.json

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+{
+  "_name_or_path": "google/vit-base-patch16-224",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "cats",
+    "1": "dogs"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "cats": "0",
+    "dogs": "1"
+  },
+  "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": "4.46.1"
+}

model.safetensors

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+size 343223968

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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+size 5176