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meat_calssify_fresh_crop_V_0_4

Image Classification
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vit
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  1. README.md +125 -0
  2. config.json +34 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +36 -0
  5. runs/Jun09_00-14-13_DESKTOP-QA5IM1O/events.out.tfevents.1717863254.DESKTOP-QA5IM1O.7160.0 +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_V_0_4
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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: 0.7935483870967742
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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_V_0_4
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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: 1.3588
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+ - Accuracy: 0.7935
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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: 1
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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: 50
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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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+ | 1.0748 | 1.0 | 617 | 0.9992 | 0.5290 |
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+ | 1.0075 | 2.0 | 1234 | 1.1657 | 0.4774 |
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+ | 1.1387 | 3.0 | 1851 | 1.7110 | 0.3355 |
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+ | 1.2272 | 4.0 | 2468 | 1.0090 | 0.5032 |
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+ | 1.1872 | 5.0 | 3085 | 1.0040 | 0.5871 |
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+ | 1.1936 | 6.0 | 3702 | 1.4017 | 0.5484 |
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+ | 1.1596 | 7.0 | 4319 | 1.2642 | 0.5935 |
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+ | 1.1932 | 8.0 | 4936 | 1.5967 | 0.5161 |
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+ | 1.1215 | 9.0 | 5553 | 1.4047 | 0.6194 |
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+ | 1.097 | 10.0 | 6170 | 1.2934 | 0.5806 |
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+ | 1.0044 | 11.0 | 6787 | 1.3448 | 0.6323 |
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+ | 0.8965 | 12.0 | 7404 | 1.3799 | 0.6645 |
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+ | 0.9943 | 13.0 | 8021 | 1.3963 | 0.6581 |
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+ | 0.9558 | 14.0 | 8638 | 1.7787 | 0.5742 |
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+ | 0.8692 | 15.0 | 9255 | 1.4618 | 0.6516 |
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+ | 0.8126 | 16.0 | 9872 | 1.2486 | 0.7097 |
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+ | 0.8093 | 17.0 | 10489 | 1.1204 | 0.7226 |
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+ | 0.6681 | 18.0 | 11106 | 1.7933 | 0.6452 |
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+ | 0.5894 | 19.0 | 11723 | 1.2285 | 0.7355 |
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+ | 0.4993 | 20.0 | 12340 | 1.7193 | 0.6516 |
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+ | 0.4736 | 21.0 | 12957 | 1.7766 | 0.6774 |
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+ | 0.4952 | 22.0 | 13574 | 1.8535 | 0.6516 |
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+ | 0.5312 | 23.0 | 14191 | 1.7282 | 0.6774 |
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+ | 0.3942 | 24.0 | 14808 | 1.9881 | 0.6516 |
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+ | 0.4166 | 25.0 | 15425 | 1.6196 | 0.6903 |
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+ | 0.4656 | 26.0 | 16042 | 1.6721 | 0.6774 |
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+ | 0.326 | 27.0 | 16659 | 2.1897 | 0.6387 |
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+ | 0.3692 | 28.0 | 17276 | 1.6734 | 0.6968 |
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+ | 0.3956 | 29.0 | 17893 | 1.6272 | 0.7290 |
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+ | 0.3108 | 30.0 | 18510 | 1.6487 | 0.7548 |
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+ | 0.2318 | 31.0 | 19127 | 1.8501 | 0.6968 |
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+ | 0.3835 | 32.0 | 19744 | 1.7877 | 0.6774 |
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+ | 0.3779 | 33.0 | 20361 | 1.4747 | 0.7355 |
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+ | 0.2913 | 34.0 | 20978 | 1.6122 | 0.7355 |
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+ | 0.275 | 35.0 | 21595 | 1.9130 | 0.6839 |
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+ | 0.2483 | 36.0 | 22212 | 1.9305 | 0.6839 |
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+ | 0.2389 | 37.0 | 22829 | 1.5973 | 0.7419 |
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+ | 0.3375 | 38.0 | 23446 | 1.2684 | 0.7742 |
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+ | 0.1867 | 39.0 | 24063 | 1.7777 | 0.7484 |
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+ | 0.2066 | 40.0 | 24680 | 1.5134 | 0.7613 |
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+ | 0.2555 | 41.0 | 25297 | 1.9315 | 0.6839 |
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+ | 0.1508 | 42.0 | 25914 | 1.6165 | 0.7484 |
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+ | 0.1262 | 43.0 | 26531 | 1.8465 | 0.7290 |
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+ | 0.1113 | 44.0 | 27148 | 2.0645 | 0.7161 |
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+ | 0.1692 | 45.0 | 27765 | 1.7539 | 0.7484 |
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+ | 0.0973 | 46.0 | 28382 | 2.0104 | 0.7161 |
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+ | 0.166 | 47.0 | 28999 | 1.6435 | 0.7742 |
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+ | 0.1476 | 48.0 | 29616 | 1.6865 | 0.7677 |
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+ | 0.1616 | 49.0 | 30233 | 2.1759 | 0.6903 |
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+ | 0.1715 | 50.0 | 30850 | 1.3588 | 0.7935 |
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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 2.3.0
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
config.json ADDED
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+ "ViTForImageClassification"
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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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+ "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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+ "layer_norm_eps": 1e-12,
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+ "model_type": "vit",
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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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