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hushem_1x_deit_tiny_adamax_lr00001_fold5

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  1. README.md +111 -0
  2. model.safetensors +1 -1
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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/deit-tiny-patch16-224
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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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+ model-index:
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+ - name: hushem_1x_deit_tiny_adamax_lr00001_fold5
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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: test
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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: 0.4634146341463415
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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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+ # hushem_1x_deit_tiny_adamax_lr00001_fold5
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+
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+ This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2718
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+ - Accuracy: 0.4634
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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: 1e-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: 50
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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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+ | No log | 0.67 | 1 | 1.6411 | 0.1220 |
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+ | No log | 2.0 | 3 | 1.5318 | 0.1951 |
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+ | No log | 2.67 | 4 | 1.5063 | 0.1707 |
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+ | No log | 4.0 | 6 | 1.4764 | 0.3171 |
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+ | No log | 4.67 | 7 | 1.4625 | 0.3171 |
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+ | No log | 6.0 | 9 | 1.4352 | 0.3902 |
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+ | 1.379 | 6.67 | 10 | 1.4210 | 0.4390 |
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+ | 1.379 | 8.0 | 12 | 1.3993 | 0.4390 |
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+ | 1.379 | 8.67 | 13 | 1.3906 | 0.4390 |
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+ | 1.379 | 10.0 | 15 | 1.3747 | 0.4146 |
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+ | 1.379 | 10.67 | 16 | 1.3676 | 0.4146 |
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+ | 1.379 | 12.0 | 18 | 1.3554 | 0.4146 |
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+ | 1.379 | 12.67 | 19 | 1.3500 | 0.4146 |
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+ | 1.107 | 14.0 | 21 | 1.3389 | 0.4146 |
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+ | 1.107 | 14.67 | 22 | 1.3348 | 0.4146 |
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+ | 1.107 | 16.0 | 24 | 1.3265 | 0.4390 |
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+ | 1.107 | 16.67 | 25 | 1.3236 | 0.4634 |
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+ | 1.107 | 18.0 | 27 | 1.3162 | 0.4634 |
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+ | 1.107 | 18.67 | 28 | 1.3129 | 0.4390 |
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+ | 0.9495 | 20.0 | 30 | 1.3051 | 0.4390 |
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+ | 0.9495 | 20.67 | 31 | 1.3019 | 0.4390 |
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+ | 0.9495 | 22.0 | 33 | 1.2961 | 0.4390 |
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+ | 0.9495 | 22.67 | 34 | 1.2934 | 0.4634 |
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+ | 0.9495 | 24.0 | 36 | 1.2879 | 0.4390 |
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+ | 0.9495 | 24.67 | 37 | 1.2851 | 0.4390 |
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+ | 0.9495 | 26.0 | 39 | 1.2815 | 0.4390 |
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+ | 0.8401 | 26.67 | 40 | 1.2802 | 0.4390 |
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+ | 0.8401 | 28.0 | 42 | 1.2775 | 0.4390 |
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+ | 0.8401 | 28.67 | 43 | 1.2761 | 0.4390 |
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+ | 0.8401 | 30.0 | 45 | 1.2740 | 0.4390 |
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+ | 0.8401 | 30.67 | 46 | 1.2734 | 0.4390 |
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+ | 0.8401 | 32.0 | 48 | 1.2723 | 0.4634 |
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+ | 0.8401 | 32.67 | 49 | 1.2719 | 0.4634 |
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+ | 0.7816 | 33.33 | 50 | 1.2718 | 0.4634 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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