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End of training

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README.md ADDED
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+ ---
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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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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ - precision
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+ model-index:
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+ - name: convnextv2-tiny-1k-224-finetuned-topwear-v2
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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: 0.8177083333333334
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+ - name: Precision
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+ type: precision
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+ value: 0.8427431106605461
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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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+ # convnextv2-tiny-1k-224-finetuned-topwear-v2
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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 the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5060
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+ - Accuracy: 0.8177
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+ - Precision: 0.8427
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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: 2e-05
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+ - train_batch_size: 10
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+ - eval_batch_size: 4
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+ - seed: 42
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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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+ - num_epochs: 100
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|
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+ | No log | 1.0 | 77 | 1.4963 | 0.6615 | 0.7047 |
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+ | No log | 2.0 | 154 | 1.0708 | 0.6354 | 0.7218 |
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+ | No log | 3.0 | 231 | 0.8045 | 0.7708 | 0.8080 |
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+ | No log | 4.0 | 308 | 0.6572 | 0.7969 | 0.8195 |
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+ | No log | 5.0 | 385 | 0.5992 | 0.7969 | 0.8338 |
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+ | No log | 6.0 | 462 | 0.5877 | 0.8021 | 0.8398 |
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+ | 0.8831 | 7.0 | 539 | 0.5497 | 0.8073 | 0.8614 |
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+ | 0.8831 | 8.0 | 616 | 0.5412 | 0.8073 | 0.8275 |
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+ | 0.8831 | 9.0 | 693 | 0.5060 | 0.8177 | 0.8427 |
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+ | 0.8831 | 10.0 | 770 | 0.5167 | 0.8281 | 0.8372 |
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+ | 0.8831 | 11.0 | 847 | 0.6315 | 0.7969 | 0.8148 |
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+ | 0.8831 | 12.0 | 924 | 0.5166 | 0.8125 | 0.8318 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.0
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+ - Pytorch 2.4.0
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
all_results.json ADDED
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+ {
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+ "epoch": 12.0,
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+ "eval_accuracy": 0.8177083333333334,
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+ "eval_loss": 0.5060345530509949,
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+ "eval_precision": 0.8427431106605461,
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+ "eval_runtime": 4.5274,
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+ "eval_samples_per_second": 42.408,
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+ "eval_steps_per_second": 10.602
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+ }
config.json ADDED
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+ {
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+ "_name_or_path": "facebook/convnextv2-tiny-1k-224",
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+ "architectures": [
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+ "ConvNextV2ForImageClassification"
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+ ],
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+ "depths": [
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+ 3,
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+ 3,
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+ 9,
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+ 3
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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": "cardigan",
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+ "1": "kurta",
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+ "2": "kurti",
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+ "3": "poncho",
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+ "4": "shirt",
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+ "5": "sweatshirt_hoodie",
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+ "6": "tshirt",
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+ "7": "tunic"
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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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+ "cardigan": 0,
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+ "kurta": 1,
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+ "kurti": 2,
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+ "poncho": 3,
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+ "shirt": 4,
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+ "sweatshirt_hoodie": 5,
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+ "tshirt": 6,
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+ "tunic": 7
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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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+ 4
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+ ],
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+ "patch_size": 4,
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+ "problem_type": "single_label_classification",
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+ "stage_names": [
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+ "stem",
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+ "stage1",
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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": "4.44.0"
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+ }
eval_results.json ADDED
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+ {
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+ "epoch": 12.0,
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+ "eval_accuracy": 0.8177083333333334,
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+ "eval_loss": 0.5060345530509949,
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+ "eval_precision": 0.8427431106605461,
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+ "eval_runtime": 4.5274,
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+ "eval_samples_per_second": 42.408,
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+ "eval_steps_per_second": 10.602
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+ }
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preprocessor_config.json ADDED
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+ "do_normalize": true,
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+ "image_mean": [
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+ "image_processor_type": "ConvNextImageProcessor",
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+ "resample": 3,
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