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hushem_5x_beit_base_adamax_0001_fold1

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  1. README.md +125 -0
  2. model.safetensors +1 -1
  3. runs/Nov27_22-15-53_0a7ba84d0833/events.out.tfevents.1701123363.0a7ba84d0833.1449.0 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/beit-base-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_5x_beit_base_adamax_0001_fold1
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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: 0.8
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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_5x_beit_base_adamax_0001_fold1
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+
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+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9719
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+ - Accuracy: 0.8
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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: 32
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+ - eval_batch_size: 32
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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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+ - 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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+ | 0.4817 | 1.0 | 27 | 0.8446 | 0.6889 |
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+ | 0.1236 | 2.0 | 54 | 0.5416 | 0.8 |
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+ | 0.0728 | 3.0 | 81 | 1.1383 | 0.7333 |
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+ | 0.0137 | 4.0 | 108 | 0.8130 | 0.7556 |
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+ | 0.0121 | 5.0 | 135 | 1.0498 | 0.7778 |
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+ | 0.0052 | 6.0 | 162 | 1.2025 | 0.7333 |
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+ | 0.0025 | 7.0 | 189 | 1.8500 | 0.6889 |
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+ | 0.0027 | 8.0 | 216 | 1.2581 | 0.7333 |
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+ | 0.0011 | 9.0 | 243 | 1.0128 | 0.7111 |
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+ | 0.0002 | 10.0 | 270 | 1.1087 | 0.7111 |
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+ | 0.0015 | 11.0 | 297 | 1.5799 | 0.6889 |
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+ | 0.0003 | 12.0 | 324 | 1.1596 | 0.7333 |
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+ | 0.0003 | 13.0 | 351 | 0.7321 | 0.8222 |
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+ | 0.0002 | 14.0 | 378 | 0.7110 | 0.8444 |
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+ | 0.0001 | 15.0 | 405 | 0.9712 | 0.8 |
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+ | 0.0001 | 16.0 | 432 | 0.9021 | 0.8 |
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+ | 0.0003 | 17.0 | 459 | 1.0755 | 0.7778 |
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+ | 0.0001 | 18.0 | 486 | 0.9553 | 0.8 |
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+ | 0.0001 | 19.0 | 513 | 0.7418 | 0.8 |
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+ | 0.0001 | 20.0 | 540 | 0.8008 | 0.8222 |
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+ | 0.0001 | 21.0 | 567 | 0.8246 | 0.8222 |
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+ | 0.0002 | 22.0 | 594 | 1.0106 | 0.8 |
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+ | 0.0006 | 23.0 | 621 | 1.3939 | 0.7111 |
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+ | 0.0001 | 24.0 | 648 | 1.1381 | 0.7111 |
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+ | 0.0002 | 25.0 | 675 | 1.0384 | 0.7556 |
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+ | 0.0001 | 26.0 | 702 | 0.9699 | 0.7556 |
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+ | 0.0001 | 27.0 | 729 | 0.8959 | 0.7778 |
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+ | 0.0 | 28.0 | 756 | 0.8640 | 0.8 |
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+ | 0.0 | 29.0 | 783 | 0.8622 | 0.8 |
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+ | 0.0001 | 30.0 | 810 | 1.0310 | 0.7778 |
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+ | 0.0001 | 31.0 | 837 | 1.1256 | 0.7778 |
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+ | 0.0001 | 32.0 | 864 | 1.0777 | 0.7778 |
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+ | 0.0001 | 33.0 | 891 | 0.9925 | 0.7556 |
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+ | 0.0001 | 34.0 | 918 | 0.9854 | 0.7778 |
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+ | 0.0 | 35.0 | 945 | 0.9843 | 0.7778 |
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+ | 0.0 | 36.0 | 972 | 0.9861 | 0.7778 |
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+ | 0.0 | 37.0 | 999 | 1.0844 | 0.8222 |
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+ | 0.0 | 38.0 | 1026 | 1.0708 | 0.8222 |
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+ | 0.0001 | 39.0 | 1053 | 1.0786 | 0.8 |
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+ | 0.0 | 40.0 | 1080 | 1.0854 | 0.8 |
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+ | 0.001 | 41.0 | 1107 | 1.0589 | 0.8 |
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+ | 0.0001 | 42.0 | 1134 | 1.1362 | 0.7556 |
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+ | 0.0028 | 43.0 | 1161 | 1.0635 | 0.8 |
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+ | 0.0 | 44.0 | 1188 | 0.9767 | 0.8 |
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+ | 0.0 | 45.0 | 1215 | 0.9696 | 0.8 |
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+ | 0.0003 | 46.0 | 1242 | 0.9742 | 0.8 |
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+ | 0.0 | 47.0 | 1269 | 0.9715 | 0.8 |
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+ | 0.0 | 48.0 | 1296 | 0.9720 | 0.8 |
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+ | 0.0001 | 49.0 | 1323 | 0.9719 | 0.8 |
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+ | 0.0001 | 50.0 | 1350 | 0.9719 | 0.8 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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