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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: microsoft/cvt-13 |
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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: cvt-13-normal |
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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: 0.7790294627383015 |
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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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# cvt-13-normal |
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This model is a fine-tuned version of [microsoft/cvt-13](https://huggingface.co/microsoft/cvt-13) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0613 |
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- Accuracy: 0.7790 |
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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: 0.0005 |
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- train_batch_size: 142 |
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- eval_batch_size: 142 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 568 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 7 | 0.8652 | 0.7946 | |
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| 2.3799 | 2.0 | 14 | 0.8683 | 0.7912 | |
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| 2.4491 | 3.0 | 21 | 0.8807 | 0.7825 | |
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| 2.4491 | 4.0 | 28 | 0.9120 | 0.7851 | |
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| 2.3011 | 5.0 | 35 | 0.9865 | 0.7565 | |
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| 2.5444 | 6.0 | 42 | 0.9863 | 0.7643 | |
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| 2.5444 | 7.0 | 49 | 1.1580 | 0.7513 | |
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| 2.4127 | 8.0 | 56 | 1.1091 | 0.7383 | |
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| 2.8757 | 9.0 | 63 | 1.0644 | 0.7496 | |
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| 2.5231 | 10.0 | 70 | 1.0888 | 0.7400 | |
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| 2.5231 | 11.0 | 77 | 1.0668 | 0.7548 | |
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| 2.7538 | 12.0 | 84 | 1.0946 | 0.7435 | |
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| 2.7032 | 13.0 | 91 | 1.0676 | 0.7608 | |
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| 2.7032 | 14.0 | 98 | 1.0409 | 0.7426 | |
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| 2.4581 | 15.0 | 105 | 1.0679 | 0.7548 | |
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| 2.7023 | 16.0 | 112 | 1.0129 | 0.7487 | |
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| 2.7023 | 17.0 | 119 | 1.1501 | 0.7366 | |
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| 2.5456 | 18.0 | 126 | 1.0452 | 0.7426 | |
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| 2.7061 | 19.0 | 133 | 1.0034 | 0.7565 | |
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| 2.3491 | 20.0 | 140 | 1.0389 | 0.7574 | |
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| 2.3491 | 21.0 | 147 | 0.9999 | 0.7782 | |
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| 2.4926 | 22.0 | 154 | 1.0131 | 0.7652 | |
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| 2.5111 | 23.0 | 161 | 1.0940 | 0.7340 | |
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| 2.5111 | 24.0 | 168 | 1.0786 | 0.7582 | |
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| 2.3443 | 25.0 | 175 | 1.0768 | 0.7617 | |
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| 2.5738 | 26.0 | 182 | 0.9781 | 0.7782 | |
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| 2.5738 | 27.0 | 189 | 0.9955 | 0.7574 | |
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| 2.3528 | 28.0 | 196 | 1.0117 | 0.7669 | |
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| 2.599 | 29.0 | 203 | 1.0806 | 0.7660 | |
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| 2.3279 | 30.0 | 210 | 1.0101 | 0.7738 | |
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| 2.3279 | 31.0 | 217 | 1.0981 | 0.7617 | |
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| 2.5649 | 32.0 | 224 | 1.0185 | 0.7782 | |
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| 2.5432 | 33.0 | 231 | 1.1070 | 0.7591 | |
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| 2.5432 | 34.0 | 238 | 1.0705 | 0.7626 | |
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| 2.3521 | 35.0 | 245 | 1.0749 | 0.7574 | |
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| 2.5948 | 36.0 | 252 | 1.0508 | 0.7626 | |
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| 2.5948 | 37.0 | 259 | 1.0374 | 0.7712 | |
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| 2.3305 | 38.0 | 266 | 1.0249 | 0.7643 | |
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| 2.4833 | 39.0 | 273 | 1.0345 | 0.7712 | |
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| 2.1504 | 40.0 | 280 | 1.0252 | 0.7617 | |
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| 2.1504 | 41.0 | 287 | 1.0361 | 0.7574 | |
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| 2.4083 | 42.0 | 294 | 0.9939 | 0.7678 | |
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| 2.37 | 43.0 | 301 | 1.0186 | 0.7695 | |
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| 2.37 | 44.0 | 308 | 1.0861 | 0.7643 | |
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| 2.2043 | 45.0 | 315 | 1.0182 | 0.7643 | |
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| 2.3554 | 46.0 | 322 | 1.0584 | 0.7539 | |
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| 2.3554 | 47.0 | 329 | 1.0541 | 0.7617 | |
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| 2.1541 | 48.0 | 336 | 1.0967 | 0.7686 | |
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| 2.3739 | 49.0 | 343 | 1.1266 | 0.7721 | |
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| 2.1028 | 50.0 | 350 | 1.1116 | 0.7652 | |
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| 2.1028 | 51.0 | 357 | 1.0804 | 0.7643 | |
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| 2.3381 | 52.0 | 364 | 1.1142 | 0.7556 | |
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| 2.2902 | 53.0 | 371 | 1.1135 | 0.7652 | |
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| 2.2902 | 54.0 | 378 | 1.1024 | 0.7461 | |
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| 2.2452 | 55.0 | 385 | 1.0722 | 0.7626 | |
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| 2.4121 | 56.0 | 392 | 1.1089 | 0.7704 | |
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| 2.4121 | 57.0 | 399 | 1.0923 | 0.7548 | |
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| 2.2067 | 58.0 | 406 | 1.0811 | 0.7591 | |
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| 2.3894 | 59.0 | 413 | 1.1097 | 0.7634 | |
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| 2.2188 | 60.0 | 420 | 1.0988 | 0.7643 | |
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| 2.2188 | 61.0 | 427 | 1.0558 | 0.7686 | |
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| 2.2859 | 62.0 | 434 | 1.0569 | 0.7695 | |
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| 2.2293 | 63.0 | 441 | 1.1053 | 0.7643 | |
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| 2.2293 | 64.0 | 448 | 1.0962 | 0.7652 | |
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| 2.136 | 65.0 | 455 | 1.0505 | 0.7756 | |
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| 2.2507 | 66.0 | 462 | 1.0425 | 0.7799 | |
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| 2.2507 | 67.0 | 469 | 1.0703 | 0.7756 | |
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| 2.0269 | 68.0 | 476 | 1.0826 | 0.7695 | |
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| 2.2972 | 69.0 | 483 | 1.0569 | 0.7747 | |
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| 2.0192 | 70.0 | 490 | 1.0773 | 0.7695 | |
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| 2.0192 | 71.0 | 497 | 1.1000 | 0.7669 | |
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| 2.3668 | 72.0 | 504 | 1.1048 | 0.7712 | |
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| 2.1285 | 73.0 | 511 | 1.0883 | 0.7712 | |
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| 2.1285 | 74.0 | 518 | 1.0893 | 0.7738 | |
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| 2.0487 | 75.0 | 525 | 1.0644 | 0.7799 | |
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| 2.2508 | 76.0 | 532 | 1.0686 | 0.7764 | |
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| 2.2508 | 77.0 | 539 | 1.0759 | 0.7764 | |
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| 2.0141 | 78.0 | 546 | 1.0673 | 0.7756 | |
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| 2.1662 | 79.0 | 553 | 1.0610 | 0.7842 | |
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| 2.0567 | 80.0 | 560 | 1.0571 | 0.7851 | |
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| 2.0567 | 81.0 | 567 | 1.0682 | 0.7799 | |
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| 2.2602 | 82.0 | 574 | 1.0700 | 0.7782 | |
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| 2.3018 | 83.0 | 581 | 1.0703 | 0.7790 | |
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| 2.3018 | 84.0 | 588 | 1.0597 | 0.7825 | |
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| 2.0309 | 85.0 | 595 | 1.0560 | 0.7825 | |
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| 2.108 | 85.8 | 600 | 1.0613 | 0.7790 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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