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Zainajabroh
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image_emotion_classification_project_4

Image Classification
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vit
Generated from Trainer
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  1. README.md +84 -0
  2. config.json +44 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +22 -0
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: google/vit-large-patch16-224-in21k
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: image_emotion_classification_project_4
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.51875
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # image_emotion_classification_project_4
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+
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+ This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.9052
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+ - Accuracy: 0.5188
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: reduce_lr_on_plateau
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+ - lr_scheduler_warmup_steps: 50
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.6977 | 1.0 | 640 | 1.5713 | 0.325 |
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+ | 1.7006 | 2.0 | 1280 | 1.4543 | 0.4562 |
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+ | 1.6725 | 3.0 | 1920 | 1.6124 | 0.4625 |
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+ | 1.2312 | 4.0 | 2560 | 1.6711 | 0.5 |
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+ | 0.6097 | 5.0 | 3200 | 1.8838 | 0.5312 |
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+ | 1.264 | 6.0 | 3840 | 2.0933 | 0.4875 |
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+ | 2.4064 | 7.0 | 4480 | 2.0628 | 0.5188 |
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+ | 2.0741 | 8.0 | 5120 | 2.6505 | 0.4625 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.2
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+ - Pytorch 2.5.0+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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+ {
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+ "_name_or_path": "google/vit-large-patch16-224-in21k",
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+ "architectures": [
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+ "ViTForImageClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "encoder_stride": 16,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 1024,
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+ "id2label": {
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+ "0": "anger",
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+ "1": "contempt",
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+ "2": "disgust",
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+ "3": "fear",
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+ "4": "happy",
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+ "5": "neutral",
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+ "6": "sad",
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+ "7": "surprise"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 4096,
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+ "label2id": {
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+ "anger": "0",
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+ "contempt": "1",
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+ "disgust": "2",
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+ "fear": "3",
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+ "happy": "4",
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+ "neutral": "5",
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+ "sad": "6",
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+ "surprise": "7"
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "vit",
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+ "num_attention_heads": 16,
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+ "num_channels": 3,
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+ "num_hidden_layers": 24,
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+ "patch_size": 16,
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+ "problem_type": "single_label_classification",
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+ "qkv_bias": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.46.2"
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+ }
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