End of training

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: image_classification
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: en-US
+      split: train
+      args: en-US
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.60625
+---
+
+<!-- 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. -->
+
+# image_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 the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1918
+- Accuracy: 0.6062
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 20   | 1.6651          | 0.3187   |
+| No log        | 2.0   | 40   | 1.3900          | 0.475    |
+| No log        | 3.0   | 60   | 1.2950          | 0.4875   |
+| No log        | 4.0   | 80   | 1.2170          | 0.5813   |
+| No log        | 5.0   | 100  | 1.1709          | 0.5687   |
+| No log        | 6.0   | 120  | 1.2711          | 0.525    |
+| No log        | 7.0   | 140  | 1.1324          | 0.575    |
+| No log        | 8.0   | 160  | 1.2349          | 0.5437   |
+| No log        | 9.0   | 180  | 1.3844          | 0.5312   |
+| No log        | 10.0  | 200  | 1.2460          | 0.55     |
+| No log        | 11.0  | 220  | 1.2182          | 0.6125   |
+| No log        | 12.0  | 240  | 1.3365          | 0.5563   |
+| No log        | 13.0  | 260  | 1.2137          | 0.6125   |
+| No log        | 14.0  | 280  | 1.3335          | 0.575    |
+| No log        | 15.0  | 300  | 1.1078          | 0.625    |
+| No log        | 16.0  | 320  | 1.2962          | 0.6      |
+| No log        | 17.0  | 340  | 1.2558          | 0.6125   |
+| No log        | 18.0  | 360  | 1.3949          | 0.55     |
+| No log        | 19.0  | 380  | 1.3807          | 0.5687   |
+| No log        | 20.0  | 400  | 1.2734          | 0.6      |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

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": "anger",
+    "1": "contempt",
+    "2": "disgust",
+    "3": "fear",
+    "4": "happy",
+    "5": "neutral",
+    "6": "sad",
+    "7": "surprise"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "anger": "0",
+    "contempt": "1",
+    "disgust": "2",
+    "fear": "3",
+    "happy": "4",
+    "neutral": "5",
+    "sad": "6",
+    "surprise": "7"
+  },
+  "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": "4.33.2"
+}

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
+  }
+}

pytorch_model.bin

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+size 343287149

training_args.bin

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