End of training

README.md

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+---
+base_model: victor/autotrain-donut-vs-croissant-1417653460
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: donat-croissant
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.988950276243094
+---
+
+<!-- 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. -->
+
+# donat-croissant
+
+This model is a fine-tuned version of [victor/autotrain-donut-vs-croissant-1417653460](https://huggingface.co/victor/autotrain-donut-vs-croissant-1417653460) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0189
+- Accuracy: 0.9890
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "victor/autotrain-donut-vs-croissant-1417653460",
+  "architectures": [
+    "SwinForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "depths": [
+    2,
+    2,
+    18,
+    2
+  ],
+  "drop_path_rate": 0.1,
+  "embed_dim": 128,
+  "encoder_stride": 32,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "croissant",
+    "1": "donut"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "croissant": "0",
+    "donut": "1"
+  },
+  "layer_norm_eps": 1e-05,
+  "max_length": 128,
+  "mlp_ratio": 4.0,
+  "model_type": "swin",
+  "num_channels": 3,
+  "num_heads": [
+    4,
+    8,
+    16,
+    32
+  ],
+  "num_layers": 4,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "padding": "max_length",
+  "patch_size": 4,
+  "path_norm": true,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.2",
+  "use_absolute_embeddings": false,
+  "window_size": 7
+}

model.safetensors

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+oid sha256:0164aead56d4f8d05e2473c751fdb6c8c5604d976b0e2ffee0c268013b38d39c
+size 347498816

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

runs/Feb28_15-34-21_e399aa6b32e3/events.out.tfevents.1709134502.e399aa6b32e3.325.0

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runs/Feb28_15-34-21_e399aa6b32e3/events.out.tfevents.1709136510.e399aa6b32e3.325.1

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training_args.bin

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