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Melo1512
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vit-msn-small-wbc-classifier-100

Image Classification
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vit_msn
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: Melo1512/vit-msn-small-wbc-blur-detector
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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: vit-msn-small-wbc-classifier-100
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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: 0.916605705925384
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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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+ # vit-msn-small-wbc-classifier-100
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+
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+ This model is a fine-tuned version of [Melo1512/vit-msn-small-wbc-blur-detector](https://huggingface.co/Melo1512/vit-msn-small-wbc-blur-detector) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5372
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+ - Accuracy: 0.9166
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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: 5e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 256
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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: 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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+ | 0.2356 | 1.0 | 208 | 0.2005 | 0.9272 |
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+ | 0.2305 | 2.0 | 416 | 0.2259 | 0.9195 |
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+ | 0.246 | 3.0 | 624 | 0.2097 | 0.9210 |
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+ | 0.2585 | 4.0 | 832 | 0.2184 | 0.9180 |
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+ | 0.2593 | 5.0 | 1040 | 0.2331 | 0.9171 |
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+ | 0.2483 | 6.0 | 1248 | 0.2170 | 0.9198 |
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+ | 0.268 | 7.0 | 1456 | 0.2228 | 0.9181 |
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+ | 0.3112 | 8.0 | 1664 | 0.2361 | 0.9171 |
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+ | 0.2679 | 9.0 | 1872 | 0.2273 | 0.9185 |
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+ | 0.3099 | 10.0 | 2080 | 0.2303 | 0.9144 |
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+ | 0.2749 | 11.0 | 2288 | 0.2658 | 0.9125 |
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+ | 0.2475 | 12.0 | 2496 | 0.2247 | 0.9179 |
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+ | 0.2338 | 13.0 | 2704 | 0.2333 | 0.9139 |
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+ | 0.2731 | 14.0 | 2912 | 0.2295 | 0.9153 |
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+ | 0.229 | 15.0 | 3120 | 0.2505 | 0.9138 |
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+ | 0.2462 | 16.0 | 3328 | 0.2534 | 0.9137 |
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+ | 0.2274 | 17.0 | 3536 | 0.2652 | 0.9079 |
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+ | 0.2339 | 18.0 | 3744 | 0.2550 | 0.9153 |
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+ | 0.2053 | 19.0 | 3952 | 0.2819 | 0.9106 |
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+ | 0.2063 | 20.0 | 4160 | 0.2747 | 0.9129 |
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+ | 0.1964 | 21.0 | 4368 | 0.2975 | 0.9118 |
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+ | 0.1953 | 22.0 | 4576 | 0.2799 | 0.9145 |
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+ | 0.1938 | 23.0 | 4784 | 0.3197 | 0.9100 |
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+ | 0.1851 | 24.0 | 4992 | 0.3143 | 0.9138 |
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+ | 0.1931 | 25.0 | 5200 | 0.3331 | 0.9125 |
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+ | 0.1877 | 26.0 | 5408 | 0.3044 | 0.9110 |
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+ | 0.177 | 27.0 | 5616 | 0.3271 | 0.9109 |
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+ | 0.1529 | 28.0 | 5824 | 0.3382 | 0.9094 |
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+ | 0.1684 | 29.0 | 6032 | 0.3415 | 0.9128 |
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+ | 0.176 | 30.0 | 6240 | 0.3463 | 0.9095 |
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+ | 0.1496 | 31.0 | 6448 | 0.3952 | 0.9136 |
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+ | 0.1509 | 32.0 | 6656 | 0.3690 | 0.9121 |
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+ | 0.1463 | 33.0 | 6864 | 0.3999 | 0.9094 |
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+ | 0.1354 | 34.0 | 7072 | 0.3996 | 0.9135 |
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+ | 0.1546 | 35.0 | 7280 | 0.3810 | 0.9116 |
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+ | 0.1513 | 36.0 | 7488 | 0.3992 | 0.9121 |
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+ | 0.115 | 37.0 | 7696 | 0.4295 | 0.9132 |
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+ | 0.1479 | 38.0 | 7904 | 0.4363 | 0.9123 |
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+ | 0.1455 | 39.0 | 8112 | 0.4220 | 0.9140 |
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+ | 0.1353 | 40.0 | 8320 | 0.4112 | 0.9127 |
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+ | 0.141 | 41.0 | 8528 | 0.4322 | 0.9139 |
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+ | 0.1272 | 42.0 | 8736 | 0.4176 | 0.9119 |
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+ | 0.1402 | 43.0 | 8944 | 0.4041 | 0.9108 |
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+ | 0.1236 | 44.0 | 9152 | 0.4478 | 0.9095 |
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+ | 0.1349 | 45.0 | 9360 | 0.4211 | 0.9112 |
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+ | 0.1472 | 46.0 | 9568 | 0.4510 | 0.9113 |
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+ | 0.1115 | 47.0 | 9776 | 0.4373 | 0.9119 |
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+ | 0.1122 | 48.0 | 9984 | 0.4689 | 0.9129 |
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+ | 0.1297 | 49.0 | 10192 | 0.4569 | 0.9140 |
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+ | 0.1337 | 50.0 | 10400 | 0.4622 | 0.9111 |
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+ | 0.1194 | 51.0 | 10608 | 0.4579 | 0.9151 |
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+ | 0.1322 | 52.0 | 10816 | 0.4728 | 0.9104 |
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+ | 0.1179 | 53.0 | 11024 | 0.4729 | 0.9125 |
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+ | 0.1216 | 54.0 | 11232 | 0.5199 | 0.9114 |
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+ | 0.1234 | 55.0 | 11440 | 0.4769 | 0.9135 |
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+ | 0.1125 | 56.0 | 11648 | 0.4871 | 0.9118 |
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+ | 0.1234 | 57.0 | 11856 | 0.4667 | 0.9146 |
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+ | 0.1103 | 58.0 | 12064 | 0.4741 | 0.9119 |
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+ | 0.1103 | 59.0 | 12272 | 0.4864 | 0.9129 |
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+ | 0.1222 | 60.0 | 12480 | 0.4550 | 0.9143 |
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+ | 0.127 | 61.0 | 12688 | 0.4919 | 0.9135 |
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+ | 0.1117 | 62.0 | 12896 | 0.4946 | 0.9139 |
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+ | 0.1078 | 63.0 | 13104 | 0.5040 | 0.9133 |
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+ | 0.1127 | 64.0 | 13312 | 0.4804 | 0.9126 |
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+ | 0.1122 | 65.0 | 13520 | 0.4997 | 0.9136 |
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+ | 0.1089 | 66.0 | 13728 | 0.5134 | 0.9139 |
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+ | 0.1179 | 67.0 | 13936 | 0.5246 | 0.9155 |
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+ | 0.0934 | 68.0 | 14144 | 0.5158 | 0.9126 |
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+ | 0.1011 | 69.0 | 14352 | 0.5361 | 0.9140 |
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+ | 0.1063 | 70.0 | 14560 | 0.5326 | 0.9135 |
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+ | 0.1021 | 71.0 | 14768 | 0.5151 | 0.9143 |
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+ | 0.1007 | 72.0 | 14976 | 0.5390 | 0.9143 |
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+ | 0.0946 | 73.0 | 15184 | 0.5256 | 0.9114 |
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+ | 0.097 | 74.0 | 15392 | 0.5247 | 0.9135 |
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+ | 0.0967 | 75.0 | 15600 | 0.5154 | 0.9144 |
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+ | 0.0985 | 76.0 | 15808 | 0.5412 | 0.9154 |
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+ | 0.0856 | 77.0 | 16016 | 0.5335 | 0.9148 |
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+ | 0.103 | 78.0 | 16224 | 0.5210 | 0.9162 |
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+ | 0.1033 | 79.0 | 16432 | 0.5165 | 0.9156 |
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+ | 0.109 | 80.0 | 16640 | 0.5303 | 0.9150 |
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+ | 0.0999 | 81.0 | 16848 | 0.5299 | 0.9158 |
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+ | 0.0966 | 82.0 | 17056 | 0.5324 | 0.9167 |
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+ | 0.0952 | 83.0 | 17264 | 0.5229 | 0.9168 |
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+ | 0.1071 | 84.0 | 17472 | 0.5303 | 0.9176 |
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+ | 0.0899 | 85.0 | 17680 | 0.5228 | 0.9160 |
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+ | 0.0868 | 86.0 | 17888 | 0.5297 | 0.9149 |
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+ | 0.1011 | 87.0 | 18096 | 0.5370 | 0.9156 |
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+ | 0.0867 | 88.0 | 18304 | 0.5430 | 0.9158 |
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+ | 0.0936 | 89.0 | 18512 | 0.5346 | 0.9165 |
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+ | 0.0929 | 90.0 | 18720 | 0.5387 | 0.9163 |
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+ | 0.0792 | 91.0 | 18928 | 0.5459 | 0.9150 |
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+ | 0.0918 | 92.0 | 19136 | 0.5257 | 0.9165 |
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+ | 0.0853 | 93.0 | 19344 | 0.5426 | 0.9155 |
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+ | 0.0908 | 94.0 | 19552 | 0.5429 | 0.9153 |
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+ | 0.0981 | 95.0 | 19760 | 0.5394 | 0.9155 |
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+ | 0.0825 | 96.0 | 19968 | 0.5345 | 0.9168 |
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+ | 0.0849 | 97.0 | 20176 | 0.5388 | 0.9164 |
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+ | 0.0992 | 98.0 | 20384 | 0.5357 | 0.9168 |
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+ | 0.0909 | 99.0 | 20592 | 0.5375 | 0.9167 |
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+ | 0.0861 | 100.0 | 20800 | 0.5372 | 0.9166 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.19.1
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