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test-hasy-5

Image Classification
Transformers
Safetensors
vit
Generated from Trainer
Inference Endpoints
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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-in21k
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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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+ model-index:
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+ - name: test-hasy-5
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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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+ # test-hasy-5
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7391
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+ - Accuracy: 0.7921
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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: 2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 1787
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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: 100
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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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+ | 3.9645 | 1.0 | 541 | 3.4295 | 0.3971 |
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+ | 3.4258 | 2.0 | 1082 | 2.8790 | 0.4782 |
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+ | 3.04 | 3.0 | 1623 | 2.4893 | 0.5468 |
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+ | 2.793 | 4.0 | 2164 | 2.2006 | 0.5738 |
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+ | 2.5551 | 5.0 | 2705 | 1.9056 | 0.6341 |
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+ | 2.3662 | 6.0 | 3246 | 1.7023 | 0.6632 |
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+ | 2.1965 | 7.0 | 3787 | 1.5740 | 0.6798 |
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+ | 2.1397 | 8.0 | 4328 | 1.4561 | 0.6944 |
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+ | 1.9955 | 9.0 | 4869 | 1.3203 | 0.7235 |
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+ | 1.9282 | 10.0 | 5410 | 1.2246 | 0.7380 |
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+ | 1.8368 | 11.0 | 5951 | 1.1823 | 0.7380 |
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+ | 1.812 | 12.0 | 6492 | 1.1298 | 0.7214 |
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+ | 1.7195 | 13.0 | 7033 | 1.0423 | 0.7484 |
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+ | 1.6314 | 14.0 | 7574 | 1.0077 | 0.7422 |
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+ | 1.5979 | 15.0 | 8115 | 1.0051 | 0.7464 |
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+ | 1.5656 | 16.0 | 8656 | 0.9325 | 0.7692 |
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+ | 1.5414 | 17.0 | 9197 | 0.8889 | 0.7734 |
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+ | 1.5342 | 18.0 | 9738 | 0.9073 | 0.7484 |
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+ | 1.4898 | 19.0 | 10279 | 0.8426 | 0.7713 |
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+ | 1.4731 | 20.0 | 10820 | 0.8625 | 0.7443 |
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+ | 1.451 | 21.0 | 11361 | 0.8015 | 0.7630 |
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+ | 1.4578 | 22.0 | 11902 | 0.8520 | 0.7588 |
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+ | 1.4126 | 23.0 | 12443 | 0.7928 | 0.7713 |
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+ | 1.3626 | 24.0 | 12984 | 0.7544 | 0.7838 |
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+ | 1.3694 | 25.0 | 13525 | 0.7699 | 0.7775 |
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+ | 1.3612 | 26.0 | 14066 | 0.7602 | 0.7775 |
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+ | 1.2963 | 27.0 | 14607 | 0.7532 | 0.7713 |
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+ | 1.3009 | 28.0 | 15148 | 0.7013 | 0.7921 |
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+ | 1.2598 | 29.0 | 15689 | 0.7085 | 0.7796 |
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+ | 1.2565 | 30.0 | 16230 | 0.7023 | 0.7775 |
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+ | 1.2735 | 31.0 | 16771 | 0.7048 | 0.7775 |
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+ | 1.2743 | 32.0 | 17312 | 0.6794 | 0.7921 |
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+ | 1.2441 | 33.0 | 17853 | 0.6932 | 0.7859 |
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+ | 1.2282 | 34.0 | 18394 | 0.7039 | 0.7942 |
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+ | 1.2204 | 35.0 | 18935 | 0.6861 | 0.8067 |
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+ | 1.1808 | 36.0 | 19476 | 0.6590 | 0.7963 |
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+ | 1.1928 | 37.0 | 20017 | 0.6784 | 0.7817 |
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+ | 1.1914 | 38.0 | 20558 | 0.6559 | 0.7963 |
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+ | 1.1856 | 39.0 | 21099 | 0.6769 | 0.7963 |
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+ | 1.1585 | 40.0 | 21640 | 0.6498 | 0.8004 |
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+ | 1.1713 | 41.0 | 22181 | 0.6447 | 0.7921 |
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+ | 1.1183 | 42.0 | 22722 | 0.6748 | 0.7713 |
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+ | 1.1564 | 43.0 | 23263 | 0.6545 | 0.7921 |
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+ | 1.1215 | 44.0 | 23804 | 0.6690 | 0.7879 |
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+ | 1.1008 | 45.0 | 24345 | 0.6598 | 0.7879 |
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+ | 1.1344 | 46.0 | 24886 | 0.6550 | 0.8025 |
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+ | 1.126 | 47.0 | 25427 | 0.6521 | 0.7859 |
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+ | 1.125 | 48.0 | 25968 | 0.6813 | 0.7817 |
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+ | 1.0855 | 49.0 | 26509 | 0.6419 | 0.7859 |
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+ | 1.0452 | 50.0 | 27050 | 0.6551 | 0.8004 |
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+ | 1.0626 | 51.0 | 27591 | 0.6675 | 0.7921 |
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+ | 1.0155 | 52.0 | 28132 | 0.6946 | 0.7921 |
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+ | 1.0319 | 53.0 | 28673 | 0.6942 | 0.7796 |
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+ | 1.0488 | 54.0 | 29214 | 0.6496 | 0.7983 |
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+ | 1.0558 | 55.0 | 29755 | 0.6465 | 0.8046 |
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+ | 0.9913 | 56.0 | 30296 | 0.6654 | 0.7921 |
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+ | 1.0555 | 57.0 | 30837 | 0.6561 | 0.7963 |
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+ | 0.9803 | 58.0 | 31378 | 0.6732 | 0.7942 |
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+ | 1.0393 | 59.0 | 31919 | 0.6893 | 0.7817 |
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+ | 0.9677 | 60.0 | 32460 | 0.6824 | 0.8046 |
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+ | 1.0082 | 61.0 | 33001 | 0.6618 | 0.7942 |
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+ | 1.0096 | 62.0 | 33542 | 0.6691 | 0.7838 |
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+ | 0.9685 | 63.0 | 34083 | 0.6793 | 0.8025 |
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+ | 0.9847 | 64.0 | 34624 | 0.6895 | 0.7838 |
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+ | 0.9639 | 65.0 | 35165 | 0.7297 | 0.7734 |
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+ | 0.9776 | 66.0 | 35706 | 0.6561 | 0.7921 |
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+ | 1.0074 | 67.0 | 36247 | 0.6999 | 0.7775 |
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+ | 0.9466 | 68.0 | 36788 | 0.6881 | 0.7942 |
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+ | 0.9425 | 69.0 | 37329 | 0.6806 | 0.7963 |
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+ | 0.9594 | 70.0 | 37870 | 0.7202 | 0.7900 |
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+ | 0.9311 | 71.0 | 38411 | 0.7162 | 0.7755 |
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+ | 0.9429 | 72.0 | 38952 | 0.7284 | 0.7921 |
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+ | 0.9666 | 73.0 | 39493 | 0.6871 | 0.7963 |
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+ | 0.945 | 74.0 | 40034 | 0.6779 | 0.7942 |
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+ | 0.9387 | 75.0 | 40575 | 0.7358 | 0.7942 |
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+ | 0.9132 | 76.0 | 41116 | 0.7044 | 0.7942 |
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+ | 0.9181 | 77.0 | 41657 | 0.7041 | 0.7963 |
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+ | 0.9218 | 78.0 | 42198 | 0.6986 | 0.7942 |
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+ | 0.8621 | 79.0 | 42739 | 0.6909 | 0.8004 |
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+ | 0.9236 | 80.0 | 43280 | 0.7136 | 0.7983 |
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+ | 0.8667 | 81.0 | 43821 | 0.7009 | 0.8025 |
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+ | 0.8856 | 82.0 | 44362 | 0.7128 | 0.7921 |
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+ | 0.917 | 83.0 | 44903 | 0.7135 | 0.7983 |
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+ | 0.8835 | 84.0 | 45444 | 0.7295 | 0.7900 |
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+ | 0.8879 | 85.0 | 45985 | 0.7450 | 0.7900 |
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+ | 0.8764 | 86.0 | 46526 | 0.7362 | 0.7942 |
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+ | 0.8674 | 87.0 | 47067 | 0.7232 | 0.7942 |
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+ | 0.8583 | 88.0 | 47608 | 0.7408 | 0.7942 |
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+ | 0.881 | 89.0 | 48149 | 0.7378 | 0.8004 |
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+ | 0.8668 | 90.0 | 48690 | 0.7473 | 0.7900 |
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+ | 0.8779 | 91.0 | 49231 | 0.7438 | 0.7983 |
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+ | 0.8717 | 92.0 | 49772 | 0.7390 | 0.8004 |
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+ | 0.8781 | 93.0 | 50313 | 0.7474 | 0.7983 |
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+ | 0.8845 | 94.0 | 50854 | 0.7446 | 0.7900 |
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+ | 0.8623 | 95.0 | 51395 | 0.7316 | 0.7921 |
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+ | 0.8341 | 96.0 | 51936 | 0.7457 | 0.7879 |
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+ | 0.8766 | 97.0 | 52477 | 0.7436 | 0.7921 |
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+ | 0.8681 | 98.0 | 53018 | 0.7484 | 0.7900 |
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+ | 0.8635 | 99.0 | 53559 | 0.7392 | 0.7942 |
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+ | 0.8091 | 100.0 | 54100 | 0.7391 | 0.7921 |
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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 2.1.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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