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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: V3_Image_classification__points_durs__google_vit-base-patch16-224-in21k |
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results: [] |
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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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# V3_Image_classification__points_durs__google_vit-base-patch16-224-in21k |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0411 |
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- Accuracy: 0.9927 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.6667 | 1.0 | 15 | 0.5893 | 0.9121 | |
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| 0.4394 | 2.0 | 30 | 0.3294 | 0.9487 | |
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| 0.2685 | 3.0 | 45 | 0.1365 | 0.9707 | |
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| 0.0936 | 4.0 | 60 | 0.0752 | 0.9853 | |
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| 0.0517 | 5.0 | 75 | 0.0553 | 0.9890 | |
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| 0.0436 | 6.0 | 90 | 0.0556 | 0.9890 | |
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| 0.018 | 7.0 | 105 | 0.0557 | 0.9890 | |
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| 0.0189 | 8.0 | 120 | 0.0457 | 0.9890 | |
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| 0.013 | 9.0 | 135 | 0.0343 | 0.9927 | |
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| 0.0115 | 10.0 | 150 | 0.0270 | 0.9963 | |
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| 0.0101 | 11.0 | 165 | 0.0355 | 0.9927 | |
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| 0.0085 | 12.0 | 180 | 0.0356 | 0.9927 | |
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| 0.0079 | 13.0 | 195 | 0.0259 | 0.9963 | |
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| 0.0069 | 14.0 | 210 | 0.0345 | 0.9927 | |
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| 0.0066 | 15.0 | 225 | 0.0360 | 0.9927 | |
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| 0.0061 | 16.0 | 240 | 0.0359 | 0.9927 | |
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| 0.0059 | 17.0 | 255 | 0.0360 | 0.9927 | |
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| 0.0055 | 18.0 | 270 | 0.0368 | 0.9927 | |
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| 0.0054 | 19.0 | 285 | 0.0375 | 0.9927 | |
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| 0.0051 | 20.0 | 300 | 0.0375 | 0.9927 | |
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| 0.0049 | 21.0 | 315 | 0.0380 | 0.9927 | |
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| 0.0047 | 22.0 | 330 | 0.0380 | 0.9927 | |
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| 0.0046 | 23.0 | 345 | 0.0383 | 0.9927 | |
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| 0.0044 | 24.0 | 360 | 0.0386 | 0.9927 | |
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| 0.0043 | 25.0 | 375 | 0.0388 | 0.9927 | |
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| 0.0041 | 26.0 | 390 | 0.0388 | 0.9927 | |
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| 0.0041 | 27.0 | 405 | 0.0391 | 0.9927 | |
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| 0.0039 | 28.0 | 420 | 0.0392 | 0.9927 | |
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| 0.0038 | 29.0 | 435 | 0.0396 | 0.9927 | |
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| 0.0037 | 30.0 | 450 | 0.0397 | 0.9927 | |
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| 0.0037 | 31.0 | 465 | 0.0397 | 0.9927 | |
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| 0.0036 | 32.0 | 480 | 0.0399 | 0.9927 | |
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| 0.0035 | 33.0 | 495 | 0.0401 | 0.9927 | |
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| 0.0034 | 34.0 | 510 | 0.0402 | 0.9927 | |
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| 0.0034 | 35.0 | 525 | 0.0403 | 0.9927 | |
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| 0.0033 | 36.0 | 540 | 0.0403 | 0.9927 | |
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| 0.0033 | 37.0 | 555 | 0.0405 | 0.9927 | |
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| 0.0032 | 38.0 | 570 | 0.0406 | 0.9927 | |
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| 0.0032 | 39.0 | 585 | 0.0406 | 0.9927 | |
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| 0.0031 | 40.0 | 600 | 0.0407 | 0.9927 | |
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| 0.0031 | 41.0 | 615 | 0.0408 | 0.9927 | |
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| 0.0031 | 42.0 | 630 | 0.0408 | 0.9927 | |
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| 0.003 | 43.0 | 645 | 0.0409 | 0.9927 | |
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| 0.003 | 44.0 | 660 | 0.0410 | 0.9927 | |
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| 0.003 | 45.0 | 675 | 0.0410 | 0.9927 | |
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| 0.003 | 46.0 | 690 | 0.0410 | 0.9927 | |
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| 0.003 | 47.0 | 705 | 0.0410 | 0.9927 | |
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| 0.0029 | 48.0 | 720 | 0.0411 | 0.9927 | |
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| 0.0029 | 49.0 | 735 | 0.0411 | 0.9927 | |
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| 0.0029 | 50.0 | 750 | 0.0411 | 0.9927 | |
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### Framework versions |
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- Transformers 4.30.0 |
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- Pytorch 2.1.1 |
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- Datasets 2.15.0 |
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- Tokenizers 0.13.3 |
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