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rathi2023
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finetuned-amazon

Image Classification
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End of training

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  1. README.md +76 -0
  2. config.json +0 -0
  3. model.safetensors +3 -0
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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
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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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+ - f1
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+ model-index:
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+ - name: finetuned-amazon
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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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+ # finetuned-amazon
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.7690
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+ - Accuracy: 0.1038
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+ - F1: 0.0409
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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: 0.0002
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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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: 4
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+ - mixed_precision_training: Native AMP
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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 | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 2.7793 | 0.27 | 100 | 2.7709 | 0.0390 | 0.0241 |
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+ | 2.773 | 0.54 | 200 | 2.7767 | 0.0410 | 0.0230 |
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+ | 2.7752 | 0.81 | 300 | 2.7872 | 0.0 | 0.0 |
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+ | 2.7731 | 1.08 | 400 | 2.7793 | 0.0171 | 0.0111 |
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+ | 2.7744 | 1.34 | 500 | 2.7733 | 0.0886 | 0.0507 |
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+ | 2.7755 | 1.61 | 600 | 2.7740 | 0.0733 | 0.0376 |
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+ | 2.7706 | 1.88 | 700 | 2.7755 | 0.0657 | 0.0401 |
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+ | 2.7723 | 2.15 | 800 | 2.7690 | 0.1038 | 0.0409 |
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+ | 2.7732 | 2.42 | 900 | 2.7738 | 0.1010 | 0.0410 |
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+ | 2.7738 | 2.69 | 1000 | 2.7729 | 0.0914 | 0.0384 |
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+ | 2.7734 | 2.96 | 1100 | 2.7732 | 0.0581 | 0.0343 |
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+ | 2.7723 | 3.23 | 1200 | 2.7726 | 0.0638 | 0.0361 |
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+ | 2.7725 | 3.49 | 1300 | 2.7731 | 0.0667 | 0.0297 |
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+ | 2.7725 | 3.76 | 1400 | 2.7734 | 0.0476 | 0.0296 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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