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hushem_5x_beit_base_rms_0001_fold1

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  1. README.md +125 -0
  2. model.safetensors +1 -1
  3. runs/Nov29_05-45-07_ac8792add2e0/events.out.tfevents.1701236708.ac8792add2e0.2336.18 +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_rms_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: 0.35555555555555557
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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_rms_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: 3.6811
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+ - Accuracy: 0.3556
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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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+ | 1.4287 | 1.0 | 27 | 1.3926 | 0.2222 |
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+ | 1.3907 | 2.0 | 54 | 1.3975 | 0.2667 |
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+ | 1.358 | 3.0 | 81 | 1.5093 | 0.2444 |
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+ | 1.3416 | 4.0 | 108 | 1.5118 | 0.2444 |
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+ | 1.2056 | 5.0 | 135 | 1.4928 | 0.2444 |
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+ | 1.1299 | 6.0 | 162 | 1.6562 | 0.2222 |
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+ | 1.1641 | 7.0 | 189 | 1.5947 | 0.2444 |
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+ | 1.1473 | 8.0 | 216 | 1.5964 | 0.2444 |
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+ | 1.1298 | 9.0 | 243 | 1.7663 | 0.2444 |
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+ | 1.1045 | 10.0 | 270 | 1.6309 | 0.3778 |
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+ | 0.8985 | 11.0 | 297 | 1.6908 | 0.4 |
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+ | 0.7744 | 12.0 | 324 | 1.3949 | 0.3556 |
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+ | 0.7617 | 13.0 | 351 | 1.4646 | 0.3778 |
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+ | 0.6843 | 14.0 | 378 | 1.5910 | 0.3778 |
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+ | 0.6647 | 15.0 | 405 | 1.8050 | 0.4 |
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+ | 0.6363 | 16.0 | 432 | 1.7016 | 0.3333 |
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+ | 0.6362 | 17.0 | 459 | 1.8539 | 0.3778 |
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+ | 0.6858 | 18.0 | 486 | 1.8678 | 0.3556 |
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+ | 0.7039 | 19.0 | 513 | 1.5776 | 0.3556 |
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+ | 0.6292 | 20.0 | 540 | 1.8552 | 0.3111 |
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+ | 0.4567 | 21.0 | 567 | 1.7854 | 0.3556 |
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+ | 0.5954 | 22.0 | 594 | 2.4822 | 0.3556 |
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+ | 0.5737 | 23.0 | 621 | 2.0564 | 0.4 |
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+ | 0.4941 | 24.0 | 648 | 1.9451 | 0.3111 |
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+ | 0.523 | 25.0 | 675 | 2.0359 | 0.3778 |
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+ | 0.5221 | 26.0 | 702 | 2.1184 | 0.4 |
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+ | 0.4589 | 27.0 | 729 | 2.0471 | 0.3556 |
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+ | 0.4473 | 28.0 | 756 | 2.5353 | 0.3556 |
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+ | 0.4328 | 29.0 | 783 | 2.7479 | 0.3556 |
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+ | 0.4259 | 30.0 | 810 | 2.2239 | 0.3778 |
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+ | 0.3698 | 31.0 | 837 | 2.5363 | 0.3556 |
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+ | 0.3577 | 32.0 | 864 | 2.5264 | 0.3556 |
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+ | 0.3882 | 33.0 | 891 | 2.2649 | 0.3333 |
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+ | 0.3526 | 34.0 | 918 | 2.6438 | 0.3556 |
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+ | 0.2747 | 35.0 | 945 | 2.3584 | 0.3778 |
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+ | 0.2842 | 36.0 | 972 | 2.8515 | 0.3556 |
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+ | 0.2603 | 37.0 | 999 | 2.3416 | 0.3778 |
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+ | 0.2268 | 38.0 | 1026 | 2.7485 | 0.3778 |
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+ | 0.2 | 39.0 | 1053 | 3.3636 | 0.3333 |
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+ | 0.2049 | 40.0 | 1080 | 3.1692 | 0.3333 |
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+ | 0.1369 | 41.0 | 1107 | 3.3885 | 0.3556 |
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+ | 0.1813 | 42.0 | 1134 | 3.3020 | 0.3333 |
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+ | 0.1518 | 43.0 | 1161 | 2.8618 | 0.4 |
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+ | 0.0986 | 44.0 | 1188 | 3.2902 | 0.3778 |
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+ | 0.131 | 45.0 | 1215 | 3.3898 | 0.3333 |
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+ | 0.0809 | 46.0 | 1242 | 3.5629 | 0.3333 |
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+ | 0.048 | 47.0 | 1269 | 3.7516 | 0.3333 |
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+ | 0.038 | 48.0 | 1296 | 3.6814 | 0.3556 |
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+ | 0.0465 | 49.0 | 1323 | 3.6811 | 0.3556 |
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+ | 0.0644 | 50.0 | 1350 | 3.6811 | 0.3556 |
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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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