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meat_calssify_fresh_crop_fixed_epoch100_V_0_8

Image Classification
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vit
Generated from Trainer
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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/Jun16_15-46-35_DESKTOP-QA5IM1O/events.out.tfevents.1718523996.DESKTOP-QA5IM1O.17380.0 +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_epoch100_V_0_8
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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: 0.8481012658227848
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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_epoch100_V_0_8
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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: 0.5407
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+ - Accuracy: 0.8481
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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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+ | 1.0983 | 1.0 | 10 | 1.0923 | 0.3861 |
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+ | 1.0837 | 2.0 | 20 | 1.0603 | 0.4937 |
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+ | 1.0593 | 3.0 | 30 | 1.0236 | 0.5633 |
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+ | 1.0323 | 4.0 | 40 | 0.9905 | 0.5696 |
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+ | 0.991 | 5.0 | 50 | 0.9442 | 0.5759 |
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+ | 0.9535 | 6.0 | 60 | 0.9318 | 0.5506 |
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+ | 0.8994 | 7.0 | 70 | 0.8444 | 0.6139 |
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+ | 0.847 | 8.0 | 80 | 0.8550 | 0.6266 |
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+ | 0.8083 | 9.0 | 90 | 0.8252 | 0.6456 |
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+ | 0.7465 | 10.0 | 100 | 0.7622 | 0.6646 |
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+ | 0.6872 | 11.0 | 110 | 0.7461 | 0.6329 |
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+ | 0.6664 | 12.0 | 120 | 0.7210 | 0.6899 |
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+ | 0.5655 | 13.0 | 130 | 0.6896 | 0.6962 |
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+ | 0.5541 | 14.0 | 140 | 0.6891 | 0.6962 |
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+ | 0.5162 | 15.0 | 150 | 0.6646 | 0.7468 |
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+ | 0.531 | 16.0 | 160 | 0.6972 | 0.6962 |
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+ | 0.4662 | 17.0 | 170 | 0.5651 | 0.7658 |
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+ | 0.4806 | 18.0 | 180 | 0.7426 | 0.6709 |
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+ | 0.405 | 19.0 | 190 | 0.6764 | 0.7089 |
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+ | 0.3897 | 20.0 | 200 | 0.5832 | 0.7658 |
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+ | 0.327 | 21.0 | 210 | 0.5591 | 0.7532 |
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+ | 0.3542 | 22.0 | 220 | 0.6793 | 0.7278 |
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+ | 0.3309 | 23.0 | 230 | 0.5890 | 0.7532 |
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+ | 0.3384 | 24.0 | 240 | 0.5595 | 0.7722 |
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+ | 0.2867 | 25.0 | 250 | 0.5669 | 0.7975 |
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+ | 0.2651 | 26.0 | 260 | 0.6369 | 0.7468 |
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+ | 0.2659 | 27.0 | 270 | 0.7925 | 0.6709 |
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+ | 0.3057 | 28.0 | 280 | 0.7006 | 0.7405 |
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+ | 0.2606 | 29.0 | 290 | 0.5800 | 0.7658 |
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+ | 0.2145 | 30.0 | 300 | 0.4187 | 0.8418 |
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+ | 0.1951 | 31.0 | 310 | 0.7022 | 0.7342 |
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+ | 0.2658 | 32.0 | 320 | 0.6902 | 0.7342 |
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+ | 0.2329 | 33.0 | 330 | 0.5709 | 0.7595 |
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+ | 0.1807 | 34.0 | 340 | 0.5226 | 0.7911 |
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+ | 0.1602 | 35.0 | 350 | 0.5418 | 0.7911 |
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+ | 0.2104 | 36.0 | 360 | 0.6453 | 0.7658 |
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+ | 0.2009 | 37.0 | 370 | 0.4814 | 0.8291 |
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+ | 0.2059 | 38.0 | 380 | 0.6135 | 0.7595 |
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+ | 0.2203 | 39.0 | 390 | 0.5581 | 0.7785 |
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+ | 0.1864 | 40.0 | 400 | 0.5939 | 0.7911 |
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+ | 0.1564 | 41.0 | 410 | 0.6002 | 0.7848 |
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+ | 0.1229 | 42.0 | 420 | 0.6470 | 0.7658 |
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+ | 0.1867 | 43.0 | 430 | 0.6545 | 0.7975 |
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+ | 0.1679 | 44.0 | 440 | 0.6079 | 0.7658 |
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+ | 0.1752 | 45.0 | 450 | 0.6666 | 0.7468 |
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+ | 0.1256 | 46.0 | 460 | 0.6651 | 0.7595 |
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+ | 0.188 | 47.0 | 470 | 0.6574 | 0.7532 |
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+ | 0.1695 | 48.0 | 480 | 0.5883 | 0.7975 |
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+ | 0.1797 | 49.0 | 490 | 0.7344 | 0.7595 |
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+ | 0.1913 | 50.0 | 500 | 0.5662 | 0.8101 |
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+ | 0.1483 | 51.0 | 510 | 0.5385 | 0.8038 |
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+ | 0.1502 | 52.0 | 520 | 0.5101 | 0.8165 |
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+ | 0.1142 | 53.0 | 530 | 0.5263 | 0.8228 |
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+ | 0.0839 | 54.0 | 540 | 0.4852 | 0.8038 |
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+ | 0.1432 | 55.0 | 550 | 0.5651 | 0.8101 |
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+ | 0.1327 | 56.0 | 560 | 0.6218 | 0.7911 |
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+ | 0.0948 | 57.0 | 570 | 0.6101 | 0.7722 |
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+ | 0.1387 | 58.0 | 580 | 0.5350 | 0.8101 |
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+ | 0.0957 | 59.0 | 590 | 0.7503 | 0.7722 |
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+ | 0.1243 | 60.0 | 600 | 0.5468 | 0.7911 |
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+ | 0.1179 | 61.0 | 610 | 0.5851 | 0.8038 |
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+ | 0.128 | 62.0 | 620 | 0.5167 | 0.8291 |
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+ | 0.1018 | 63.0 | 630 | 0.5119 | 0.8481 |
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+ | 0.0987 | 64.0 | 640 | 0.6415 | 0.7911 |
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+ | 0.0901 | 65.0 | 650 | 0.6031 | 0.8038 |
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+ | 0.1457 | 66.0 | 660 | 0.6773 | 0.7848 |
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+ | 0.1247 | 67.0 | 670 | 0.5563 | 0.7975 |
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+ | 0.127 | 68.0 | 680 | 0.7763 | 0.7595 |
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+ | 0.0841 | 69.0 | 690 | 0.4934 | 0.8544 |
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+ | 0.0914 | 70.0 | 700 | 0.6510 | 0.8228 |
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+ | 0.0982 | 71.0 | 710 | 0.5742 | 0.8101 |
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+ | 0.0945 | 72.0 | 720 | 0.4954 | 0.8481 |
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+ | 0.077 | 73.0 | 730 | 0.6194 | 0.8101 |
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+ | 0.0936 | 74.0 | 740 | 0.5301 | 0.8228 |
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+ | 0.0641 | 75.0 | 750 | 0.5673 | 0.8165 |
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+ | 0.0646 | 76.0 | 760 | 0.5055 | 0.8291 |
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+ | 0.0794 | 77.0 | 770 | 0.5444 | 0.8228 |
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+ | 0.0774 | 78.0 | 780 | 0.5511 | 0.8228 |
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+ | 0.0674 | 79.0 | 790 | 0.5688 | 0.8354 |
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+ | 0.0731 | 80.0 | 800 | 0.5594 | 0.8291 |
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+ | 0.0839 | 81.0 | 810 | 0.6970 | 0.7785 |
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+ | 0.0857 | 82.0 | 820 | 0.5651 | 0.7975 |
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+ | 0.0729 | 83.0 | 830 | 0.7003 | 0.7848 |
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+ | 0.074 | 84.0 | 840 | 0.5293 | 0.8165 |
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+ | 0.0505 | 85.0 | 850 | 0.5051 | 0.8544 |
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+ | 0.0669 | 86.0 | 860 | 0.6459 | 0.8101 |
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+ | 0.0614 | 87.0 | 870 | 0.5474 | 0.8291 |
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+ | 0.0659 | 88.0 | 880 | 0.4981 | 0.8291 |
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+ | 0.0702 | 89.0 | 890 | 0.5611 | 0.8291 |
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+ | 0.0635 | 90.0 | 900 | 0.6273 | 0.7975 |
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+ | 0.0698 | 91.0 | 910 | 0.4314 | 0.8734 |
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+ | 0.0671 | 92.0 | 920 | 0.5471 | 0.8291 |
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+ | 0.057 | 93.0 | 930 | 0.4922 | 0.8481 |
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+ | 0.0563 | 94.0 | 940 | 0.5463 | 0.8418 |
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+ | 0.0638 | 95.0 | 950 | 0.5177 | 0.8291 |
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+ | 0.0545 | 96.0 | 960 | 0.6183 | 0.8038 |
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+ | 0.0534 | 97.0 | 970 | 0.5460 | 0.8165 |
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+ | 0.0655 | 98.0 | 980 | 0.4196 | 0.8861 |
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+ | 0.0775 | 99.0 | 990 | 0.5088 | 0.8354 |
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+ | 0.0519 | 100.0 | 1000 | 0.5407 | 0.8481 |
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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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+ "width": 224
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+ }
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