| | --- |
| | license: apache-2.0 |
| | base_model: google/vit-base-patch16-224-in21k |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - imagefolder |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: image_classification |
| | results: |
| | - task: |
| | name: Image Classification |
| | type: image-classification |
| | dataset: |
| | name: imagefolder |
| | type: imagefolder |
| | config: en-US |
| | split: train |
| | args: en-US |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.525 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # image_classification |
| | |
| | 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. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.9905 |
| | - Accuracy: 0.525 |
| | |
| | ## Model description |
| | |
| | More information needed |
| | |
| | ## Intended uses & limitations |
| | |
| | More information needed |
| | |
| | ## Training and evaluation data |
| | |
| | More information needed |
| | |
| | ## Training procedure |
| | |
| | ### Training hyperparameters |
| | |
| | The following hyperparameters were used during training: |
| | - learning_rate: 0.0001 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 50 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | No log | 1.0 | 40 | 1.7409 | 0.2875 | |
| | | No log | 2.0 | 80 | 1.5124 | 0.4375 | |
| | | No log | 3.0 | 120 | 1.4255 | 0.4437 | |
| | | No log | 4.0 | 160 | 1.4154 | 0.425 | |
| | | No log | 5.0 | 200 | 1.2886 | 0.4625 | |
| | | No log | 6.0 | 240 | 1.2963 | 0.5125 | |
| | | No log | 7.0 | 280 | 1.3139 | 0.55 | |
| | | No log | 8.0 | 320 | 1.2976 | 0.5312 | |
| | | No log | 9.0 | 360 | 1.4368 | 0.5062 | |
| | | No log | 10.0 | 400 | 1.4022 | 0.5062 | |
| | | No log | 11.0 | 440 | 1.2853 | 0.55 | |
| | | No log | 12.0 | 480 | 1.3265 | 0.5563 | |
| | | 0.8831 | 13.0 | 520 | 1.3894 | 0.55 | |
| | | 0.8831 | 14.0 | 560 | 1.4465 | 0.5312 | |
| | | 0.8831 | 15.0 | 600 | 1.7185 | 0.475 | |
| | | 0.8831 | 16.0 | 640 | 1.7408 | 0.4875 | |
| | | 0.8831 | 17.0 | 680 | 1.5199 | 0.5437 | |
| | | 0.8831 | 18.0 | 720 | 1.7238 | 0.525 | |
| | | 0.8831 | 19.0 | 760 | 1.8348 | 0.4875 | |
| | | 0.8831 | 20.0 | 800 | 1.6278 | 0.5125 | |
| | | 0.8831 | 21.0 | 840 | 1.7539 | 0.5 | |
| | | 0.8831 | 22.0 | 880 | 1.9007 | 0.4938 | |
| | | 0.8831 | 23.0 | 920 | 1.6903 | 0.5375 | |
| | | 0.8831 | 24.0 | 960 | 1.7954 | 0.5062 | |
| | | 0.2214 | 25.0 | 1000 | 1.7070 | 0.575 | |
| | | 0.2214 | 26.0 | 1040 | 1.6764 | 0.5625 | |
| | | 0.2214 | 27.0 | 1080 | 1.8590 | 0.5188 | |
| | | 0.2214 | 28.0 | 1120 | 1.7531 | 0.5188 | |
| | | 0.2214 | 29.0 | 1160 | 1.5238 | 0.5875 | |
| | | 0.2214 | 30.0 | 1200 | 1.6463 | 0.6 | |
| | | 0.2214 | 31.0 | 1240 | 1.7955 | 0.5563 | |
| | | 0.2214 | 32.0 | 1280 | 1.9920 | 0.5 | |
| | | 0.2214 | 33.0 | 1320 | 1.8826 | 0.55 | |
| | | 0.2214 | 34.0 | 1360 | 2.0573 | 0.5 | |
| | | 0.2214 | 35.0 | 1400 | 1.8438 | 0.5312 | |
| | | 0.2214 | 36.0 | 1440 | 1.9004 | 0.5312 | |
| | | 0.2214 | 37.0 | 1480 | 1.8215 | 0.5437 | |
| | | 0.1479 | 38.0 | 1520 | 2.0467 | 0.5437 | |
| | | 0.1479 | 39.0 | 1560 | 1.8564 | 0.5687 | |
| | | 0.1479 | 40.0 | 1600 | 1.8381 | 0.5687 | |
| | | 0.1479 | 41.0 | 1640 | 1.8110 | 0.5687 | |
| | | 0.1479 | 42.0 | 1680 | 2.0587 | 0.5375 | |
| | | 0.1479 | 43.0 | 1720 | 1.9597 | 0.5687 | |
| | | 0.1479 | 44.0 | 1760 | 1.9199 | 0.5687 | |
| | | 0.1479 | 45.0 | 1800 | 1.8714 | 0.5312 | |
| | | 0.1479 | 46.0 | 1840 | 1.9463 | 0.575 | |
| | | 0.1479 | 47.0 | 1880 | 2.0449 | 0.5312 | |
| | | 0.1479 | 48.0 | 1920 | 1.9172 | 0.525 | |
| | | 0.1479 | 49.0 | 1960 | 1.9153 | 0.55 | |
| | | 0.0946 | 50.0 | 2000 | 1.9905 | 0.525 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.33.2 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.13.3 |
| | |
