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End of training

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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-small-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_40x_deit_small_sgd_00001_fold2
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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: 0.28888888888888886
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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_40x_deit_small_sgd_00001_fold2
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+
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+ This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.4445
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+ - Accuracy: 0.2889
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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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+ - 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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+ | 1.9592 | 1.0 | 215 | 1.6375 | 0.2444 |
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+ | 1.9589 | 2.0 | 430 | 1.6244 | 0.2444 |
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+ | 1.9405 | 3.0 | 645 | 1.6119 | 0.2444 |
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+ | 1.8111 | 4.0 | 860 | 1.6000 | 0.2444 |
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+ | 1.7854 | 5.0 | 1075 | 1.5888 | 0.2444 |
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+ | 1.7837 | 6.0 | 1290 | 1.5782 | 0.2444 |
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+ | 1.8329 | 7.0 | 1505 | 1.5681 | 0.2444 |
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+ | 1.808 | 8.0 | 1720 | 1.5587 | 0.2444 |
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+ | 1.8135 | 9.0 | 1935 | 1.5499 | 0.2444 |
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+ | 1.7532 | 10.0 | 2150 | 1.5416 | 0.2444 |
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+ | 1.7679 | 11.0 | 2365 | 1.5338 | 0.2667 |
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+ | 1.6698 | 12.0 | 2580 | 1.5266 | 0.2667 |
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+ | 1.7071 | 13.0 | 2795 | 1.5198 | 0.2667 |
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+ | 1.7064 | 14.0 | 3010 | 1.5135 | 0.2667 |
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+ | 1.6474 | 15.0 | 3225 | 1.5077 | 0.2667 |
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+ | 1.6795 | 16.0 | 3440 | 1.5023 | 0.2667 |
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+ | 1.6509 | 17.0 | 3655 | 1.4973 | 0.2444 |
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+ | 1.6571 | 18.0 | 3870 | 1.4927 | 0.2444 |
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+ | 1.6903 | 19.0 | 4085 | 1.4885 | 0.2444 |
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+ | 1.594 | 20.0 | 4300 | 1.4845 | 0.2444 |
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+ | 1.6043 | 21.0 | 4515 | 1.4809 | 0.2444 |
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+ | 1.5781 | 22.0 | 4730 | 1.4775 | 0.2667 |
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+ | 1.6042 | 23.0 | 4945 | 1.4744 | 0.2667 |
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+ | 1.6585 | 24.0 | 5160 | 1.4716 | 0.2667 |
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+ | 1.6133 | 25.0 | 5375 | 1.4689 | 0.2667 |
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+ | 1.5503 | 26.0 | 5590 | 1.4665 | 0.2667 |
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+ | 1.559 | 27.0 | 5805 | 1.4642 | 0.2889 |
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+ | 1.5271 | 28.0 | 6020 | 1.4621 | 0.3111 |
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+ | 1.5368 | 29.0 | 6235 | 1.4602 | 0.3111 |
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+ | 1.5411 | 30.0 | 6450 | 1.4584 | 0.3111 |
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+ | 1.6163 | 31.0 | 6665 | 1.4568 | 0.3111 |
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+ | 1.5496 | 32.0 | 6880 | 1.4553 | 0.3111 |
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+ | 1.5517 | 33.0 | 7095 | 1.4539 | 0.3111 |
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+ | 1.5789 | 34.0 | 7310 | 1.4526 | 0.3111 |
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+ | 1.5768 | 35.0 | 7525 | 1.4515 | 0.3111 |
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+ | 1.5496 | 36.0 | 7740 | 1.4505 | 0.3111 |
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+ | 1.5074 | 37.0 | 7955 | 1.4495 | 0.3111 |
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+ | 1.5918 | 38.0 | 8170 | 1.4487 | 0.3111 |
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+ | 1.5751 | 39.0 | 8385 | 1.4479 | 0.3111 |
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+ | 1.5533 | 40.0 | 8600 | 1.4472 | 0.3111 |
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+ | 1.5217 | 41.0 | 8815 | 1.4467 | 0.3111 |
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+ | 1.5477 | 42.0 | 9030 | 1.4461 | 0.3111 |
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+ | 1.5219 | 43.0 | 9245 | 1.4457 | 0.3111 |
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+ | 1.5414 | 44.0 | 9460 | 1.4453 | 0.3111 |
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+ | 1.5697 | 45.0 | 9675 | 1.4450 | 0.3111 |
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+ | 1.5331 | 46.0 | 9890 | 1.4448 | 0.3111 |
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+ | 1.5195 | 47.0 | 10105 | 1.4446 | 0.3111 |
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+ | 1.5072 | 48.0 | 10320 | 1.4445 | 0.2889 |
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+ | 1.5469 | 49.0 | 10535 | 1.4445 | 0.2889 |
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+ | 1.5351 | 50.0 | 10750 | 1.4445 | 0.2889 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.1
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.2
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