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meat_calssify_fresh_crop_fixed_overlap_epoch100_V_0_7

Image Classification
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vit
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  1. README.md +175 -0
  2. config.json +34 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +36 -0
  5. runs/Jun15_18-25-58_DESKTOP-QA5IM1O/events.out.tfevents.1718447159.DESKTOP-QA5IM1O.1192.0 +3 -0
  6. training_args.bin +3 -0
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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+ 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: meat_calssify_fresh_crop_fixed_overlap_epoch100_V_0_7
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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: train
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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: 0.9532710280373832
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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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+ # meat_calssify_fresh_crop_fixed_overlap_epoch100_V_0_7
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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 imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1612
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+ - Accuracy: 0.9533
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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: 1
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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: 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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+ | 1.1056 | 1.0 | 21 | 1.0902 | 0.4206 |
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+ | 1.0884 | 2.0 | 42 | 1.0625 | 0.4766 |
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+ | 1.0199 | 3.0 | 63 | 1.0114 | 0.5202 |
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+ | 0.9636 | 4.0 | 84 | 0.9735 | 0.5234 |
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+ | 0.8789 | 5.0 | 105 | 0.9093 | 0.5701 |
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+ | 0.8625 | 6.0 | 126 | 0.8850 | 0.6044 |
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+ | 0.7607 | 7.0 | 147 | 0.8773 | 0.6106 |
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+ | 0.7615 | 8.0 | 168 | 0.8370 | 0.5950 |
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+ | 0.7052 | 9.0 | 189 | 0.8290 | 0.6231 |
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+ | 0.6378 | 10.0 | 210 | 0.6312 | 0.7508 |
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+ | 0.5741 | 11.0 | 231 | 0.6255 | 0.7508 |
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+ | 0.5034 | 12.0 | 252 | 0.7393 | 0.6511 |
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+ | 0.5886 | 13.0 | 273 | 0.6083 | 0.7664 |
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+ | 0.4313 | 14.0 | 294 | 0.5113 | 0.7975 |
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+ | 0.4542 | 15.0 | 315 | 0.5826 | 0.7632 |
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+ | 0.3551 | 16.0 | 336 | 0.6452 | 0.7664 |
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+ | 0.3613 | 17.0 | 357 | 0.5993 | 0.7601 |
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+ | 0.3627 | 18.0 | 378 | 0.4192 | 0.8536 |
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+ | 0.2659 | 19.0 | 399 | 0.4967 | 0.8131 |
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+ | 0.2783 | 20.0 | 420 | 0.4777 | 0.8287 |
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+ | 0.2618 | 21.0 | 441 | 0.5573 | 0.7850 |
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+ | 0.2962 | 22.0 | 462 | 0.4956 | 0.7975 |
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+ | 0.3321 | 23.0 | 483 | 0.3398 | 0.8723 |
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+ | 0.3306 | 24.0 | 504 | 0.4910 | 0.8224 |
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+ | 0.2813 | 25.0 | 525 | 0.3536 | 0.8536 |
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+ | 0.189 | 26.0 | 546 | 0.2645 | 0.8910 |
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+ | 0.2114 | 27.0 | 567 | 0.5280 | 0.8224 |
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+ | 0.2027 | 28.0 | 588 | 0.5607 | 0.8100 |
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+ | 0.204 | 29.0 | 609 | 0.3179 | 0.8879 |
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+ | 0.1844 | 30.0 | 630 | 0.2999 | 0.8972 |
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+ | 0.1655 | 31.0 | 651 | 0.3656 | 0.8785 |
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+ | 0.3034 | 32.0 | 672 | 0.2920 | 0.8941 |
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+ | 0.1617 | 33.0 | 693 | 0.3290 | 0.8847 |
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+ | 0.1588 | 34.0 | 714 | 0.2659 | 0.8972 |
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+ | 0.1263 | 35.0 | 735 | 0.4091 | 0.8505 |
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+ | 0.145 | 36.0 | 756 | 0.3294 | 0.8785 |
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+ | 0.1413 | 37.0 | 777 | 0.2408 | 0.9128 |
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+ | 0.1309 | 38.0 | 798 | 0.2980 | 0.8910 |
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+ | 0.1316 | 39.0 | 819 | 0.3839 | 0.8723 |
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+ | 0.1508 | 40.0 | 840 | 0.2546 | 0.9034 |
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+ | 0.1078 | 41.0 | 861 | 0.2317 | 0.9221 |
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+ | 0.1263 | 42.0 | 882 | 0.3212 | 0.8910 |
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+ | 0.142 | 43.0 | 903 | 0.3513 | 0.8660 |
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+ | 0.108 | 44.0 | 924 | 0.2291 | 0.9034 |
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+ | 0.1297 | 45.0 | 945 | 0.3755 | 0.8692 |
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+ | 0.1195 | 46.0 | 966 | 0.2830 | 0.9065 |
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+ | 0.1029 | 47.0 | 987 | 0.3560 | 0.8785 |
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+ | 0.0988 | 48.0 | 1008 | 0.4380 | 0.8536 |
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+ | 0.0931 | 49.0 | 1029 | 0.1965 | 0.9283 |
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+ | 0.0787 | 50.0 | 1050 | 0.3069 | 0.9003 |
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+ | 0.0925 | 51.0 | 1071 | 0.3059 | 0.9065 |
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+ | 0.0999 | 52.0 | 1092 | 0.2761 | 0.9097 |
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+ | 0.1079 | 53.0 | 1113 | 0.4334 | 0.8598 |
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+ | 0.0967 | 54.0 | 1134 | 0.2761 | 0.9097 |
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+ | 0.2187 | 55.0 | 1155 | 0.3166 | 0.8941 |
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+ | 0.2928 | 56.0 | 1176 | 0.1629 | 0.9377 |
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+ | 0.0813 | 57.0 | 1197 | 0.2661 | 0.9159 |
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+ | 0.0898 | 58.0 | 1218 | 0.1690 | 0.9315 |
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+ | 0.0741 | 59.0 | 1239 | 0.2331 | 0.9190 |
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+ | 0.0646 | 60.0 | 1260 | 0.1978 | 0.9221 |
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+ | 0.0576 | 61.0 | 1281 | 0.2079 | 0.9377 |
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+ | 0.0676 | 62.0 | 1302 | 0.2102 | 0.9315 |
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+ | 0.0716 | 63.0 | 1323 | 0.2085 | 0.9315 |
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+ | 0.1935 | 64.0 | 1344 | 0.2461 | 0.9315 |
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+ | 0.0633 | 65.0 | 1365 | 0.1748 | 0.9346 |
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+ | 0.062 | 66.0 | 1386 | 0.2004 | 0.9315 |
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+ | 0.0757 | 67.0 | 1407 | 0.2812 | 0.9034 |
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+ | 0.0548 | 68.0 | 1428 | 0.1503 | 0.9502 |
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+ | 0.0583 | 69.0 | 1449 | 0.3126 | 0.9097 |
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+ | 0.2111 | 70.0 | 1470 | 0.2005 | 0.9470 |
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+ | 0.0648 | 71.0 | 1491 | 0.1651 | 0.9533 |
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+ | 0.0477 | 72.0 | 1512 | 0.2301 | 0.9346 |
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+ | 0.0438 | 73.0 | 1533 | 0.2156 | 0.9252 |
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+ | 0.0631 | 74.0 | 1554 | 0.2343 | 0.9283 |
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+ | 0.0498 | 75.0 | 1575 | 0.2876 | 0.9065 |
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+ | 0.0605 | 76.0 | 1596 | 0.2125 | 0.9283 |
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+ | 0.0604 | 77.0 | 1617 | 0.1966 | 0.9408 |
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+ | 0.0509 | 78.0 | 1638 | 0.2012 | 0.9470 |
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+ | 0.0452 | 79.0 | 1659 | 0.2409 | 0.9315 |
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+ | 0.0419 | 80.0 | 1680 | 0.2316 | 0.9283 |
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+ | 0.0306 | 81.0 | 1701 | 0.2379 | 0.9346 |
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+ | 0.0403 | 82.0 | 1722 | 0.2128 | 0.9346 |
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+ | 0.0484 | 83.0 | 1743 | 0.1239 | 0.9502 |
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+ | 0.0523 | 84.0 | 1764 | 0.2109 | 0.9408 |
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+ | 0.0445 | 85.0 | 1785 | 0.2261 | 0.9283 |
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+ | 0.0442 | 86.0 | 1806 | 0.1753 | 0.9564 |
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+ | 0.0274 | 87.0 | 1827 | 0.1932 | 0.9408 |
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+ | 0.0395 | 88.0 | 1848 | 0.1622 | 0.9439 |
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+ | 0.0587 | 89.0 | 1869 | 0.2000 | 0.9408 |
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+ | 0.0299 | 90.0 | 1890 | 0.2348 | 0.9221 |
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+ | 0.033 | 91.0 | 1911 | 0.1726 | 0.9439 |
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+ | 0.032 | 92.0 | 1932 | 0.1737 | 0.9470 |
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+ | 0.0275 | 93.0 | 1953 | 0.1737 | 0.9470 |
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+ | 0.0324 | 94.0 | 1974 | 0.2660 | 0.9159 |
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+ | 0.0256 | 95.0 | 1995 | 0.1639 | 0.9408 |
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+ | 0.0289 | 96.0 | 2016 | 0.1312 | 0.9502 |
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+ | 0.0304 | 97.0 | 2037 | 0.1784 | 0.9439 |
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+ | 0.0411 | 98.0 | 2058 | 0.1326 | 0.9626 |
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+ | 0.0256 | 99.0 | 2079 | 0.1724 | 0.9470 |
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+ | 0.0382 | 100.0 | 2100 | 0.1612 | 0.9533 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.1
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
config.json ADDED
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+ {
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+ "_name_or_path": "google/vit-base-patch16-224-in21k",
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+ "architectures": [
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+ "ViTForImageClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "encoder_stride": 16,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "fresh1",
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+ "1": "fresh2",
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+ "2": "fresh3"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "label2id": {
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+ "fresh1": "0",
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+ "fresh2": "1",
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+ "fresh3": "2"
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "vit",
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+ "num_attention_heads": 12,
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+ "num_channels": 3,
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+ "num_hidden_layers": 12,
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+ "patch_size": 16,
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+ "problem_type": "single_label_classification",
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+ "qkv_bias": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.41.2"
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+ }
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