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vit-augmented

Image Classification
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vit
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  1. README.md +72 -0
  2. config.json +40 -0
  3. model.safetensors +3 -0
  4. runs/Oct19_02-43-37_98071d0550f1/events.out.tfevents.1729305820.98071d0550f1.1100.1 +3 -0
  5. runs/Oct19_02-45-17_98071d0550f1/events.out.tfevents.1729305920.98071d0550f1.1100.2 +3 -0
  6. runs/Oct19_02-45-39_98071d0550f1/events.out.tfevents.1729305944.98071d0550f1.1100.3 +3 -0
  7. runs/Oct19_02-45-39_98071d0550f1/events.out.tfevents.1729317895.98071d0550f1.1100.4 +3 -0
  8. training_args.bin +3 -0
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-base-patch16-224-in21k
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: vit-augmented
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+ results: []
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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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+ # vit-augmented
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7627
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+ - Accuracy: 0.8096
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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: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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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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+ | 1.2553 | 1.0 | 240 | 1.2678 | 0.4939 |
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+ | 0.9239 | 2.0 | 480 | 0.9428 | 0.6534 |
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+ | 0.5559 | 3.0 | 720 | 0.8016 | 0.7161 |
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+ | 0.303 | 4.0 | 960 | 0.7304 | 0.7509 |
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+ | 0.1581 | 5.0 | 1200 | 0.7179 | 0.7684 |
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+ | 0.1043 | 6.0 | 1440 | 0.6920 | 0.7911 |
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+ | 0.0394 | 7.0 | 1680 | 0.7819 | 0.7840 |
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+ | 0.0214 | 8.0 | 1920 | 0.7248 | 0.8047 |
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+ | 0.0173 | 9.0 | 2160 | 0.7635 | 0.8083 |
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+ | 0.0114 | 10.0 | 2400 | 0.7627 | 0.8096 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.1+cu121
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+ - Tokenizers 0.19.1
config.json ADDED
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+ {
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+ "_name_or_path": "google/vit-base-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": 768,
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+ "id2label": {
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+ "0": "LABEL_0",
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+ "1": "LABEL_1",
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+ "2": "LABEL_2",
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+ "3": "LABEL_3",
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+ "4": "LABEL_4",
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+ "5": "LABEL_5"
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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": 3072,
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+ "label2id": {
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+ "LABEL_0": 0,
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+ "LABEL_1": 1,
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+ "LABEL_2": 2,
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+ "LABEL_3": 3,
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+ "LABEL_4": 4,
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+ "LABEL_5": 5
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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": 12,
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+ "num_channels": 3,
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+ "num_hidden_layers": 12,
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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": "4.44.2"
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+ }
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