| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - imagefolder |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: resnet-50-LongSleeveCleanedData |
| | results: |
| | - task: |
| | name: Image Classification |
| | type: image-classification |
| | dataset: |
| | name: imagefolder |
| | type: imagefolder |
| | config: default |
| | split: train |
| | args: default |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.9787709497206704 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # resnet-50-LongSleeveCleanedData |
| |
|
| | This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0889 |
| | - Accuracy: 0.9788 |
| |
|
| | ## 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: 5e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 7 |
| | - total_train_batch_size: 56 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.01 |
| | - num_epochs: 20 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.9906 | 0.99 | 143 | 1.0394 | 0.6134 | |
| | | 0.7315 | 2.0 | 287 | 0.6790 | 0.7631 | |
| | | 0.559 | 3.0 | 431 | 0.4735 | 0.8547 | |
| | | 0.4905 | 4.0 | 575 | 0.3148 | 0.8983 | |
| | | 0.3465 | 5.0 | 719 | 0.2225 | 0.9363 | |
| | | 0.3372 | 6.0 | 863 | 0.1839 | 0.9486 | |
| | | 0.3349 | 7.0 | 1007 | 0.1617 | 0.9587 | |
| | | 0.3159 | 7.99 | 1150 | 0.1323 | 0.9620 | |
| | | 0.2805 | 9.0 | 1294 | 0.1660 | 0.9587 | |
| | | 0.2657 | 10.0 | 1438 | 0.1456 | 0.9531 | |
| | | 0.2929 | 11.0 | 1582 | 0.1086 | 0.9698 | |
| | | 0.2763 | 12.0 | 1726 | 0.0886 | 0.9765 | |
| | | 0.2475 | 13.0 | 1870 | 0.1041 | 0.9732 | |
| | | 0.2148 | 14.0 | 2014 | 0.0955 | 0.9777 | |
| | | 0.209 | 14.99 | 2157 | 0.1061 | 0.9709 | |
| | | 0.2408 | 16.0 | 2301 | 0.0784 | 0.9743 | |
| | | 0.222 | 17.0 | 2445 | 0.0839 | 0.9698 | |
| | | 0.208 | 18.0 | 2589 | 0.0873 | 0.9732 | |
| | | 0.2214 | 19.0 | 2733 | 0.0889 | 0.9788 | |
| | | 0.2375 | 19.88 | 2860 | 0.0864 | 0.9743 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.28.1 |
| | - Pytorch 2.0.0+cu118 |
| | - Datasets 2.12.0 |
| | - Tokenizers 0.13.3 |
| |
|
