Duplicate from trpakov/vit-face-expression

Co-authored-by: Tr Pakov <[email protected]>

.gitattributes

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README.md

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+---
+{}
+---
+# Vision Transformer (ViT) for Facial Expression Recognition Model Card
+
+## Model Overview
+
+- **Model Name:** [trpakov/vit-face-expression](https://huggingface.co/trpakov/vit-face-expression)
+
+- **Task:** Facial Expression/Emotion Recognition
+
+- **Dataset:** [FER2013](https://www.kaggle.com/datasets/msambare/fer2013)
+
+- **Model Architecture:** [Vision Transformer (ViT)](https://huggingface.co/docs/transformers/model_doc/vit)
+
+- **Finetuned from model:** [vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k)
+
+## Model Description
+
+The vit-face-expression model is a Vision Transformer fine-tuned for the task of facial emotion recognition. 
+
+It is trained on the FER2013 dataset, which consists of facial images categorized into seven different emotions:
+- Angry
+- Disgust
+- Fear
+- Happy
+- Sad
+- Surprise
+- Neutral
+
+## Data Preprocessing
+
+The input images are preprocessed before being fed into the model. The preprocessing steps include:
+- **Resizing:** Images are resized to the specified input size.
+- **Normalization:** Pixel values are normalized to a specific range.
+- **Data Augmentation:** Random transformations such as rotations, flips, and zooms are applied to augment the training dataset.
+
+## Evaluation Metrics
+
+- **Validation set accuracy:** 0.7113
+- **Test set accuracy:** 0.7116
+
+## Limitations
+
+- **Data Bias:** The model's performance may be influenced by biases present in the training data.
+- **Generalization:** The model's ability to generalize to unseen data is subject to the diversity of the training dataset.

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": "angry",
+    "1": "disgust",
+    "2": "fear",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprise"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "angry": "0",
+    "disgust": "1",
+    "fear": "2",
+    "happy": "3",
+    "neutral": "4",
+    "sad": "5",
+    "surprise": "6"
+  },
+  "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": "4.24.0"
+}

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onnx/config.json

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+{
+  "_name_or_path": "trpakov/vit-face-expression",
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+  "hidden_act": "gelu",
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+    "1": "disgust",
+    "2": "fear",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprise"
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+  "initializer_range": 0.02,
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+  "label2id": {
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+    "happy": "3",
+    "neutral": "4",
+    "sad": "5",
+    "surprise": "6"
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+  "model_type": "vit",
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+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "transformers_version": "4.34.0"
+}

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onnx/preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "feature_extractor_type": "ViTFeatureExtractor",
+  "image_mean": [
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preprocessor_config.json

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