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grateful-shape-212

Image Classification
Transformers
Safetensors
convnextv2
Generated from Trainer
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  1. README.md +73 -0
  2. best_model/config.json +53 -0
  3. best_model/model.safetensors +3 -0
  4. best_model/preprocessor_config.json +22 -0
  5. best_model/training_args.bin +3 -0
  6. model.safetensors +1 -1
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: facebook/convnextv2-tiny-1k-224
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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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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: grateful-shape-212
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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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+ # grateful-shape-212
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+
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+ This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.3777
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+ - Accuracy: 0.2708
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+ - Precision: 0.4203
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+ - Recall: 0.2708
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+ - F1: 0.3127
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+ - Roc Auc: 0.5428
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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: 0.0001
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+ - train_batch_size: 256
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+ - eval_batch_size: 256
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.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: cosine
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 5
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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 | Precision | Recall | F1 | Roc Auc |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
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+ | 1.4367 | 1.0 | 17 | 1.3810 | 0.0898 | 0.4478 | 0.0898 | 0.1092 | 0.5060 |
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+ | 1.3894 | 2.0 | 34 | 1.3751 | 0.1823 | 0.4052 | 0.1823 | 0.2266 | 0.5250 |
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+ | 1.3619 | 3.0 | 51 | 1.3766 | 0.2422 | 0.4100 | 0.2422 | 0.2876 | 0.5369 |
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+ | 1.3523 | 4.0 | 68 | 1.3776 | 0.2708 | 0.4238 | 0.2708 | 0.3132 | 0.5422 |
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+ | 1.3475 | 5.0 | 85 | 1.3777 | 0.2708 | 0.4203 | 0.2708 | 0.3127 | 0.5428 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.52.3
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+ - Pytorch 2.7.0+cpu
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+ - Datasets 3.6.0
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+ - Tokenizers 0.21.0
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+ {
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+ "architectures": [
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+ "ConvNextV2ForImageClassification"
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+ ],
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+ "depths": [
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+ ],
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+ "drop_path_rate": 0.0,
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+ "hidden_act": "gelu",
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+ "hidden_sizes": [
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+ 96,
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+ 192,
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+ 384,
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+ 768
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+ ],
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+ "id2label": {
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+ "0": "Mild_Demented",
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+ "1": "Moderate_Demented",
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+ "2": "Non_Demented",
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+ "3": "Very_Mild_Demented"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "label2id": {
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+ "Moderate_Demented": 1,
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+ "Non_Demented": 2,
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+ "Very_Mild_Demented": 3
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "convnextv2",
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+ "num_channels": 3,
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+ "num_stages": 4,
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+ "out_features": [
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+ "stage4"
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+ ],
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+ "out_indices": [
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+ "patch_size": 4,
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+ "stage_names": [
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+ "stem",
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+ "stage2",
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+ "stage3",
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+ "stage4"
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+ ],
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.52.3"
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+ }
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