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meat_calssify_fresh_crop_fixed_overlap_epoch100_V_0_13

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/Jun17_18-34-53_DESKTOP-QA5IM1O/events.out.tfevents.1718620493.DESKTOP-QA5IM1O.17096.0 +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_13
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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: 0.9595015576323987
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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_13
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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: 0.1337
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+ - Accuracy: 0.9595
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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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+ | 1.0893 | 1.0 | 21 | 1.0721 | 0.4922 |
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+ | 1.057 | 2.0 | 42 | 1.0397 | 0.5234 |
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+ | 1.018 | 3.0 | 63 | 0.9985 | 0.5265 |
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+ | 0.9639 | 4.0 | 84 | 0.9241 | 0.5794 |
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+ | 0.8882 | 5.0 | 105 | 0.8763 | 0.6231 |
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+ | 0.8154 | 6.0 | 126 | 0.8003 | 0.6542 |
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+ | 0.6905 | 7.0 | 147 | 0.8660 | 0.5981 |
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+ | 0.7078 | 8.0 | 168 | 0.7604 | 0.6729 |
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+ | 0.6762 | 9.0 | 189 | 0.7024 | 0.7134 |
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+ | 0.5977 | 10.0 | 210 | 0.7110 | 0.6854 |
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+ | 0.516 | 11.0 | 231 | 0.6112 | 0.7383 |
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+ | 0.4939 | 12.0 | 252 | 0.5301 | 0.7882 |
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+ | 0.4254 | 13.0 | 273 | 0.5863 | 0.7664 |
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+ | 0.4009 | 14.0 | 294 | 0.6802 | 0.7103 |
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+ | 0.4477 | 15.0 | 315 | 0.6327 | 0.7508 |
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+ | 0.3547 | 16.0 | 336 | 0.4456 | 0.8442 |
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+ | 0.3203 | 17.0 | 357 | 0.5052 | 0.7975 |
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+ | 0.3331 | 18.0 | 378 | 0.4561 | 0.8442 |
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+ | 0.3304 | 19.0 | 399 | 0.5010 | 0.8131 |
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+ | 0.3035 | 20.0 | 420 | 0.4363 | 0.8474 |
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+ | 0.2585 | 21.0 | 441 | 0.4671 | 0.8224 |
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+ | 0.2425 | 22.0 | 462 | 0.4404 | 0.8474 |
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+ | 0.2911 | 23.0 | 483 | 0.4463 | 0.8442 |
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+ | 0.2466 | 24.0 | 504 | 0.3739 | 0.8692 |
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+ | 0.2028 | 25.0 | 525 | 0.3317 | 0.8754 |
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+ | 0.1761 | 26.0 | 546 | 0.5032 | 0.8287 |
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+ | 0.2257 | 27.0 | 567 | 0.4841 | 0.8567 |
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+ | 0.2464 | 28.0 | 588 | 0.3266 | 0.8941 |
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+ | 0.1637 | 29.0 | 609 | 0.5122 | 0.8193 |
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+ | 0.2037 | 30.0 | 630 | 0.3683 | 0.8847 |
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+ | 0.1592 | 31.0 | 651 | 0.3185 | 0.8785 |
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+ | 0.1779 | 32.0 | 672 | 0.4130 | 0.8660 |
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+ | 0.1726 | 33.0 | 693 | 0.2861 | 0.9128 |
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+ | 0.1685 | 34.0 | 714 | 0.3174 | 0.8910 |
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+ | 0.1571 | 35.0 | 735 | 0.3252 | 0.8941 |
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+ | 0.1315 | 36.0 | 756 | 0.4721 | 0.8224 |
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+ | 0.2717 | 37.0 | 777 | 0.4957 | 0.8380 |
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+ | 0.1968 | 38.0 | 798 | 0.2139 | 0.9346 |
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+ | 0.1257 | 39.0 | 819 | 0.2550 | 0.9003 |
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+ | 0.1178 | 40.0 | 840 | 0.3248 | 0.8816 |
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+ | 0.1101 | 41.0 | 861 | 0.3600 | 0.8847 |
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+ | 0.117 | 42.0 | 882 | 0.4135 | 0.8567 |
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+ | 0.1339 | 43.0 | 903 | 0.3311 | 0.8847 |
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+ | 0.1098 | 44.0 | 924 | 0.4151 | 0.8660 |
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+ | 0.0872 | 45.0 | 945 | 0.2727 | 0.9097 |
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+ | 0.1106 | 46.0 | 966 | 0.3106 | 0.9065 |
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+ | 0.0955 | 47.0 | 987 | 0.2232 | 0.9315 |
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+ | 0.1308 | 48.0 | 1008 | 0.2594 | 0.9128 |
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+ | 0.0809 | 49.0 | 1029 | 0.2846 | 0.9065 |
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+ | 0.1123 | 50.0 | 1050 | 0.2310 | 0.9221 |
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+ | 0.0971 | 51.0 | 1071 | 0.3536 | 0.8879 |
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+ | 0.1126 | 52.0 | 1092 | 0.3048 | 0.8972 |
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+ | 0.0909 | 53.0 | 1113 | 0.2762 | 0.9097 |
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+ | 0.089 | 54.0 | 1134 | 0.2672 | 0.9065 |
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+ | 0.0881 | 55.0 | 1155 | 0.3479 | 0.8972 |
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+ | 0.0852 | 56.0 | 1176 | 0.3397 | 0.9003 |
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+ | 0.0712 | 57.0 | 1197 | 0.2242 | 0.9252 |
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+ | 0.0844 | 58.0 | 1218 | 0.2430 | 0.9221 |
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+ | 0.0619 | 59.0 | 1239 | 0.3453 | 0.8785 |
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+ | 0.0904 | 60.0 | 1260 | 0.2579 | 0.9190 |
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+ | 0.0704 | 61.0 | 1281 | 0.2337 | 0.9252 |
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+ | 0.0637 | 62.0 | 1302 | 0.2778 | 0.9128 |
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+ | 0.0752 | 63.0 | 1323 | 0.2019 | 0.9315 |
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+ | 0.0759 | 64.0 | 1344 | 0.2226 | 0.9221 |
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+ | 0.048 | 65.0 | 1365 | 0.3095 | 0.9003 |
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+ | 0.0546 | 66.0 | 1386 | 0.3657 | 0.8972 |
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+ | 0.0664 | 67.0 | 1407 | 0.3862 | 0.8972 |
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+ | 0.0584 | 68.0 | 1428 | 0.2183 | 0.9408 |
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+ | 0.0704 | 69.0 | 1449 | 0.2288 | 0.9283 |
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+ | 0.0444 | 70.0 | 1470 | 0.2355 | 0.9252 |
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+ | 0.0475 | 71.0 | 1491 | 0.1171 | 0.9626 |
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+ | 0.0594 | 72.0 | 1512 | 0.2632 | 0.9252 |
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+ | 0.0428 | 73.0 | 1533 | 0.2323 | 0.9346 |
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+ | 0.0501 | 74.0 | 1554 | 0.2586 | 0.9221 |
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+ | 0.0556 | 75.0 | 1575 | 0.2172 | 0.9252 |
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+ | 0.0427 | 76.0 | 1596 | 0.2898 | 0.9097 |
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+ | 0.0572 | 77.0 | 1617 | 0.1617 | 0.9502 |
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+ | 0.038 | 78.0 | 1638 | 0.2294 | 0.9221 |
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+ | 0.0453 | 79.0 | 1659 | 0.1670 | 0.9502 |
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+ | 0.0378 | 80.0 | 1680 | 0.1205 | 0.9595 |
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+ | 0.0444 | 81.0 | 1701 | 0.1833 | 0.9470 |
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+ | 0.065 | 82.0 | 1722 | 0.2581 | 0.9252 |
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+ | 0.0498 | 83.0 | 1743 | 0.2651 | 0.9315 |
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+ | 0.0607 | 84.0 | 1764 | 0.2678 | 0.9221 |
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+ | 0.0554 | 85.0 | 1785 | 0.1547 | 0.9470 |
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+ | 0.0313 | 86.0 | 1806 | 0.1567 | 0.9533 |
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+ | 0.0267 | 87.0 | 1827 | 0.1955 | 0.9346 |
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+ | 0.0377 | 88.0 | 1848 | 0.1900 | 0.9346 |
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+ | 0.0388 | 89.0 | 1869 | 0.1831 | 0.9377 |
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+ | 0.0297 | 90.0 | 1890 | 0.1823 | 0.9470 |
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+ | 0.0424 | 91.0 | 1911 | 0.2606 | 0.9315 |
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+ | 0.0459 | 92.0 | 1932 | 0.1478 | 0.9502 |
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+ | 0.0308 | 93.0 | 1953 | 0.1695 | 0.9439 |
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+ | 0.0415 | 94.0 | 1974 | 0.1325 | 0.9564 |
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+ | 0.0387 | 95.0 | 1995 | 0.0877 | 0.9751 |
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+ | 0.0318 | 96.0 | 2016 | 0.1765 | 0.9408 |
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+ | 0.0317 | 97.0 | 2037 | 0.1650 | 0.9564 |
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+ | 0.0198 | 98.0 | 2058 | 0.2043 | 0.9439 |
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+ | 0.0422 | 99.0 | 2079 | 0.1777 | 0.9377 |
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+ | 0.0335 | 100.0 | 2100 | 0.1337 | 0.9595 |
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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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+ "intermediate_size": 3072,
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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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