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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: google/vit-base-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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+ - f1
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+ model-index:
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+ - name: vit-base-patch16-224-in21k-finetuned-mgasior-07-02-2024
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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: F1
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+ type: f1
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+ value: 0.5354330708661418
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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-base-patch16-224-in21k-finetuned-mgasior-07-02-2024
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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 the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2283
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+ - F1: 0.5354
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 32
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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: 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 | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 1.6344 | 0.98 | 35 | 1.5842 | 0.3228 |
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+ | 1.4673 | 1.99 | 71 | 1.4140 | 0.4803 |
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+ | 1.3523 | 2.99 | 107 | 1.3067 | 0.5118 |
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+ | 1.2607 | 4.0 | 143 | 1.2424 | 0.5354 |
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+ | 1.2571 | 4.9 | 175 | 1.2283 | 0.5354 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.1
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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