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meat_calssify_fresh_crop_fixed_epoch100_V_0_6

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_14-26-41_DESKTOP-QA5IM1O/events.out.tfevents.1718519201.DESKTOP-QA5IM1O.20020.0 +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_6
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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: 0.8164556962025317
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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_6
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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: 0.5432
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+ - Accuracy: 0.8165
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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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+ | 1.1096 | 1.0 | 10 | 1.1024 | 0.3291 |
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+ | 1.0818 | 2.0 | 20 | 1.0876 | 0.4241 |
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+ | 1.0619 | 3.0 | 30 | 1.0912 | 0.3987 |
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+ | 1.0289 | 4.0 | 40 | 1.0680 | 0.4494 |
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+ | 1.0023 | 5.0 | 50 | 1.0357 | 0.4241 |
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+ | 0.9453 | 6.0 | 60 | 1.0095 | 0.4937 |
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+ | 0.8856 | 7.0 | 70 | 0.9563 | 0.5443 |
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+ | 0.8301 | 8.0 | 80 | 0.9307 | 0.5506 |
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+ | 0.7855 | 9.0 | 90 | 0.9109 | 0.5696 |
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+ | 0.7062 | 10.0 | 100 | 0.8383 | 0.5949 |
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+ | 0.6655 | 11.0 | 110 | 0.7534 | 0.7089 |
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+ | 0.617 | 12.0 | 120 | 0.8160 | 0.6646 |
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+ | 0.5821 | 13.0 | 130 | 0.7361 | 0.6962 |
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+ | 0.5097 | 14.0 | 140 | 0.7594 | 0.6899 |
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+ | 0.4944 | 15.0 | 150 | 0.7679 | 0.6709 |
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+ | 0.4787 | 16.0 | 160 | 0.6902 | 0.7595 |
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+ | 0.4234 | 17.0 | 170 | 0.8019 | 0.6835 |
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+ | 0.451 | 18.0 | 180 | 0.6534 | 0.7532 |
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+ | 0.4402 | 19.0 | 190 | 0.6980 | 0.7152 |
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+ | 0.395 | 20.0 | 200 | 0.7276 | 0.6962 |
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+ | 0.3548 | 21.0 | 210 | 0.7002 | 0.6899 |
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+ | 0.3231 | 22.0 | 220 | 0.7080 | 0.7089 |
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+ | 0.2844 | 23.0 | 230 | 0.6934 | 0.7152 |
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+ | 0.2909 | 24.0 | 240 | 0.6465 | 0.7468 |
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+ | 0.3433 | 25.0 | 250 | 0.5959 | 0.7595 |
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+ | 0.2718 | 26.0 | 260 | 0.6787 | 0.7405 |
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+ | 0.2516 | 27.0 | 270 | 0.5951 | 0.8165 |
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+ | 0.2717 | 28.0 | 280 | 0.6355 | 0.7405 |
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+ | 0.2509 | 29.0 | 290 | 0.6980 | 0.6899 |
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+ | 0.2407 | 30.0 | 300 | 0.5824 | 0.7722 |
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+ | 0.2444 | 31.0 | 310 | 0.6241 | 0.7342 |
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+ | 0.2153 | 32.0 | 320 | 0.5982 | 0.7658 |
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+ | 0.2294 | 33.0 | 330 | 0.6701 | 0.7532 |
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+ | 0.1901 | 34.0 | 340 | 0.8116 | 0.6772 |
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+ | 0.252 | 35.0 | 350 | 0.5960 | 0.7848 |
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+ | 0.1761 | 36.0 | 360 | 0.5993 | 0.7785 |
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+ | 0.1892 | 37.0 | 370 | 0.6046 | 0.7785 |
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+ | 0.15 | 38.0 | 380 | 0.6442 | 0.8038 |
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+ | 0.1705 | 39.0 | 390 | 0.7802 | 0.7152 |
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+ | 0.2171 | 40.0 | 400 | 0.7078 | 0.7278 |
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+ | 0.2233 | 41.0 | 410 | 0.5835 | 0.7785 |
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+ | 0.2252 | 42.0 | 420 | 0.7923 | 0.7089 |
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+ | 0.2304 | 43.0 | 430 | 0.6414 | 0.7342 |
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+ | 0.231 | 44.0 | 440 | 0.5405 | 0.7911 |
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+ | 0.1573 | 45.0 | 450 | 0.7065 | 0.7468 |
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+ | 0.1203 | 46.0 | 460 | 0.7642 | 0.7278 |
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+ | 0.1712 | 47.0 | 470 | 0.6204 | 0.7658 |
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+ | 0.1406 | 48.0 | 480 | 0.6591 | 0.7658 |
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+ | 0.1877 | 49.0 | 490 | 0.7968 | 0.7152 |
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+ | 0.1457 | 50.0 | 500 | 0.6790 | 0.7658 |
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+ | 0.1391 | 51.0 | 510 | 0.6116 | 0.7658 |
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+ | 0.1508 | 52.0 | 520 | 0.7331 | 0.7722 |
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+ | 0.1468 | 53.0 | 530 | 0.6900 | 0.7722 |
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+ | 0.13 | 54.0 | 540 | 0.5799 | 0.7975 |
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+ | 0.1078 | 55.0 | 550 | 0.6568 | 0.7785 |
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+ | 0.0945 | 56.0 | 560 | 0.6073 | 0.8101 |
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+ | 0.1358 | 57.0 | 570 | 0.4966 | 0.8291 |
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+ | 0.1605 | 58.0 | 580 | 0.6678 | 0.7722 |
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+ | 0.1673 | 59.0 | 590 | 0.5742 | 0.7975 |
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+ | 0.1112 | 60.0 | 600 | 0.6181 | 0.8038 |
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+ | 0.1144 | 61.0 | 610 | 0.5031 | 0.8354 |
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+ | 0.1154 | 62.0 | 620 | 0.6085 | 0.8038 |
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+ | 0.1141 | 63.0 | 630 | 0.4470 | 0.8734 |
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+ | 0.1201 | 64.0 | 640 | 0.5089 | 0.8291 |
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+ | 0.0871 | 65.0 | 650 | 0.5447 | 0.8481 |
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+ | 0.0939 | 66.0 | 660 | 0.5763 | 0.7911 |
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+ | 0.1098 | 67.0 | 670 | 0.6186 | 0.7911 |
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+ | 0.1062 | 68.0 | 680 | 0.6349 | 0.8038 |
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+ | 0.0755 | 69.0 | 690 | 0.8513 | 0.7278 |
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+ | 0.1257 | 70.0 | 700 | 0.6852 | 0.7911 |
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+ | 0.0651 | 71.0 | 710 | 0.7073 | 0.7722 |
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+ | 0.1024 | 72.0 | 720 | 0.5794 | 0.8354 |
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+ | 0.0887 | 73.0 | 730 | 0.7889 | 0.7278 |
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+ | 0.1014 | 74.0 | 740 | 0.5774 | 0.8228 |
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+ | 0.0986 | 75.0 | 750 | 0.6864 | 0.8038 |
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+ | 0.098 | 76.0 | 760 | 0.4825 | 0.8354 |
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+ | 0.1049 | 77.0 | 770 | 0.7881 | 0.7658 |
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+ | 0.0997 | 78.0 | 780 | 0.5239 | 0.8418 |
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+ | 0.0939 | 79.0 | 790 | 0.6434 | 0.8228 |
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+ | 0.0851 | 80.0 | 800 | 0.5087 | 0.8291 |
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+ | 0.0683 | 81.0 | 810 | 0.6410 | 0.7658 |
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+ | 0.084 | 82.0 | 820 | 0.6120 | 0.8101 |
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+ | 0.0717 | 83.0 | 830 | 0.6231 | 0.8038 |
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+ | 0.0811 | 84.0 | 840 | 0.4338 | 0.8544 |
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+ | 0.066 | 85.0 | 850 | 0.4633 | 0.8544 |
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+ | 0.0746 | 86.0 | 860 | 0.6960 | 0.7595 |
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+ | 0.0864 | 87.0 | 870 | 0.6154 | 0.8101 |
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+ | 0.0432 | 88.0 | 880 | 0.5864 | 0.8228 |
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+ | 0.0644 | 89.0 | 890 | 0.6045 | 0.7911 |
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+ | 0.0644 | 90.0 | 900 | 0.5924 | 0.8101 |
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+ | 0.0976 | 91.0 | 910 | 0.6515 | 0.8165 |
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+ | 0.0593 | 92.0 | 920 | 0.5491 | 0.8101 |
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+ | 0.0884 | 93.0 | 930 | 0.6618 | 0.8101 |
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+ | 0.0752 | 94.0 | 940 | 0.5612 | 0.8165 |
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+ | 0.0423 | 95.0 | 950 | 0.5914 | 0.8101 |
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+ | 0.0685 | 96.0 | 960 | 0.5502 | 0.8291 |
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+ | 0.0425 | 97.0 | 970 | 0.6455 | 0.7975 |
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+ | 0.0639 | 98.0 | 980 | 0.5402 | 0.8291 |
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+ | 0.056 | 99.0 | 990 | 0.5159 | 0.8481 |
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+ | 0.0663 | 100.0 | 1000 | 0.5432 | 0.8165 |
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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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+ }
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