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image_classification

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
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  1. README.md +53 -53
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.575
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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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 imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5646
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- - Accuracy: 0.575
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  ## Model description
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@@ -64,56 +64,56 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 40 | 1.8666 | 0.3312 |
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- | No log | 2.0 | 80 | 1.5679 | 0.4188 |
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- | No log | 3.0 | 120 | 1.4168 | 0.5062 |
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- | No log | 4.0 | 160 | 1.2966 | 0.5563 |
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- | No log | 5.0 | 200 | 1.3039 | 0.45 |
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- | No log | 6.0 | 240 | 1.2528 | 0.5188 |
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- | No log | 7.0 | 280 | 1.2559 | 0.525 |
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- | No log | 8.0 | 320 | 1.2510 | 0.55 |
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- | No log | 9.0 | 360 | 1.3209 | 0.525 |
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- | No log | 10.0 | 400 | 1.2598 | 0.5188 |
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- | No log | 11.0 | 440 | 1.3478 | 0.5 |
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- | No log | 12.0 | 480 | 1.2411 | 0.5625 |
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- | 1.0456 | 13.0 | 520 | 1.2945 | 0.575 |
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- | 1.0456 | 14.0 | 560 | 1.3332 | 0.5 |
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- | 1.0456 | 15.0 | 600 | 1.2186 | 0.5875 |
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- | 1.0456 | 16.0 | 640 | 1.2907 | 0.5563 |
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- | 1.0456 | 17.0 | 680 | 1.3378 | 0.5312 |
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- | 1.0456 | 18.0 | 720 | 1.4472 | 0.5375 |
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- | 1.0456 | 19.0 | 760 | 1.1642 | 0.6438 |
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- | 1.0456 | 20.0 | 800 | 1.2972 | 0.5437 |
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- | 1.0456 | 21.0 | 840 | 1.3696 | 0.5875 |
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- | 1.0456 | 22.0 | 880 | 1.4568 | 0.5375 |
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- | 1.0456 | 23.0 | 920 | 1.3409 | 0.5625 |
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- | 1.0456 | 24.0 | 960 | 1.3188 | 0.5687 |
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- | 0.2919 | 25.0 | 1000 | 1.4131 | 0.5813 |
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- | 0.2919 | 26.0 | 1040 | 1.3066 | 0.575 |
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- | 0.2919 | 27.0 | 1080 | 1.4908 | 0.5375 |
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- | 0.2919 | 28.0 | 1120 | 1.4409 | 0.5563 |
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- | 0.2919 | 29.0 | 1160 | 1.5531 | 0.5188 |
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- | 0.2919 | 30.0 | 1200 | 1.4412 | 0.5938 |
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- | 0.2919 | 31.0 | 1240 | 1.4300 | 0.575 |
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- | 0.2919 | 32.0 | 1280 | 1.6232 | 0.5375 |
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- | 0.2919 | 33.0 | 1320 | 1.4592 | 0.6 |
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- | 0.2919 | 34.0 | 1360 | 1.3311 | 0.6312 |
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- | 0.2919 | 35.0 | 1400 | 1.5094 | 0.5625 |
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- | 0.2919 | 36.0 | 1440 | 1.3694 | 0.6062 |
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- | 0.2919 | 37.0 | 1480 | 1.5205 | 0.5813 |
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- | 0.1643 | 38.0 | 1520 | 1.4502 | 0.6125 |
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- | 0.1643 | 39.0 | 1560 | 1.2809 | 0.6625 |
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- | 0.1643 | 40.0 | 1600 | 1.6043 | 0.5563 |
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- | 0.1643 | 41.0 | 1640 | 1.5729 | 0.5625 |
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- | 0.1643 | 42.0 | 1680 | 1.5918 | 0.5625 |
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- | 0.1643 | 43.0 | 1720 | 1.5747 | 0.575 |
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- | 0.1643 | 44.0 | 1760 | 1.6325 | 0.5437 |
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- | 0.1643 | 45.0 | 1800 | 1.5850 | 0.575 |
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- | 0.1643 | 46.0 | 1840 | 1.6558 | 0.575 |
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- | 0.1643 | 47.0 | 1880 | 1.4821 | 0.5875 |
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- | 0.1643 | 48.0 | 1920 | 1.6070 | 0.575 |
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- | 0.1643 | 49.0 | 1960 | 1.6660 | 0.525 |
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- | 0.1152 | 50.0 | 2000 | 1.5803 | 0.575 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.55
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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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  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 imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.2586
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+ - Accuracy: 0.55
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 40 | 1.8677 | 0.3688 |
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+ | No log | 2.0 | 80 | 1.5622 | 0.3625 |
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+ | No log | 3.0 | 120 | 1.4344 | 0.5375 |
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+ | No log | 4.0 | 160 | 1.2909 | 0.5 |
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+ | No log | 5.0 | 200 | 1.2146 | 0.6 |
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+ | No log | 6.0 | 240 | 1.2457 | 0.55 |
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+ | No log | 7.0 | 280 | 1.2429 | 0.5563 |
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+ | No log | 8.0 | 320 | 1.2015 | 0.5375 |
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+ | No log | 9.0 | 360 | 1.2393 | 0.5188 |
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+ | No log | 10.0 | 400 | 1.1908 | 0.5687 |
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+ | No log | 11.0 | 440 | 1.1580 | 0.6188 |
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+ | No log | 12.0 | 480 | 1.1608 | 0.575 |
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+ | 1.0532 | 13.0 | 520 | 1.2468 | 0.5687 |
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+ | 1.0532 | 14.0 | 560 | 1.2747 | 0.5188 |
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+ | 1.0532 | 15.0 | 600 | 1.3293 | 0.525 |
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+ | 1.0532 | 16.0 | 640 | 1.3720 | 0.525 |
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+ | 1.0532 | 17.0 | 680 | 1.4374 | 0.5125 |
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+ | 1.0532 | 18.0 | 720 | 1.3092 | 0.5687 |
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+ | 1.0532 | 19.0 | 760 | 1.4143 | 0.5437 |
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+ | 1.0532 | 20.0 | 800 | 1.5023 | 0.4938 |
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+ | 1.0532 | 21.0 | 840 | 1.4033 | 0.575 |
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+ | 1.0532 | 22.0 | 880 | 1.4476 | 0.5437 |
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+ | 1.0532 | 23.0 | 920 | 1.3089 | 0.5813 |
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+ | 1.0532 | 24.0 | 960 | 1.3866 | 0.5813 |
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+ | 0.3016 | 25.0 | 1000 | 1.3748 | 0.5875 |
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+ | 0.3016 | 26.0 | 1040 | 1.5846 | 0.5312 |
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+ | 0.3016 | 27.0 | 1080 | 1.3451 | 0.5875 |
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+ | 0.3016 | 28.0 | 1120 | 1.5289 | 0.5062 |
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+ | 0.3016 | 29.0 | 1160 | 1.6067 | 0.5125 |
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+ | 0.3016 | 30.0 | 1200 | 1.5002 | 0.5375 |
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+ | 0.3016 | 31.0 | 1240 | 1.5404 | 0.55 |
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+ | 0.3016 | 32.0 | 1280 | 1.5542 | 0.5563 |
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+ | 0.3016 | 33.0 | 1320 | 1.4320 | 0.6062 |
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+ | 0.3016 | 34.0 | 1360 | 1.6465 | 0.5312 |
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+ | 0.3016 | 35.0 | 1400 | 1.7259 | 0.5062 |
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+ | 0.3016 | 36.0 | 1440 | 1.5655 | 0.5687 |
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+ | 0.3016 | 37.0 | 1480 | 1.4517 | 0.6188 |
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+ | 0.1764 | 38.0 | 1520 | 1.5884 | 0.575 |
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+ | 0.1764 | 39.0 | 1560 | 1.4692 | 0.5813 |
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+ | 0.1764 | 40.0 | 1600 | 1.5062 | 0.6125 |
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+ | 0.1764 | 41.0 | 1640 | 1.5122 | 0.6 |
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+ | 0.1764 | 42.0 | 1680 | 1.5859 | 0.6 |
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+ | 0.1764 | 43.0 | 1720 | 1.6816 | 0.525 |
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+ | 0.1764 | 44.0 | 1760 | 1.5594 | 0.6062 |
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+ | 0.1764 | 45.0 | 1800 | 1.7011 | 0.5375 |
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+ | 0.1764 | 46.0 | 1840 | 1.5676 | 0.575 |
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+ | 0.1764 | 47.0 | 1880 | 1.5260 | 0.6 |
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+ | 0.1764 | 48.0 | 1920 | 1.5711 | 0.575 |
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+ | 0.1764 | 49.0 | 1960 | 1.7095 | 0.5563 |
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+ | 0.1256 | 50.0 | 2000 | 1.7625 | 0.5188 |
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  ### Framework versions
pytorch_model.bin CHANGED
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