| --- |
| license: apache-2.0 |
| base_model: microsoft/resnet-101 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: resnet-101-finetuned-CivilEng11k-newDS |
| 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: 0.9932203389830508 |
| --- |
| |
| <!-- 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-101-finetuned-CivilEng11k-newDS |
|
|
| This model is a fine-tuned version of [microsoft/resnet-101](https://huggingface.co/microsoft/resnet-101) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4541 |
| - Accuracy: 0.9932 |
|
|
| ## 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: 0.001 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 20 |
| - total_train_batch_size: 640 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 20 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 0.54 | 1 | 1.0986 | 0.4136 | |
| | No log | 1.62 | 3 | 1.0295 | 0.4339 | |
| | No log | 2.7 | 5 | 0.8537 | 0.4339 | |
| | No log | 3.78 | 7 | 0.6785 | 0.4441 | |
| | No log | 4.86 | 9 | 0.6141 | 0.6576 | |
| | No log | 5.95 | 11 | 0.5794 | 0.7559 | |
| | No log | 6.49 | 12 | 0.5616 | 0.8034 | |
| | No log | 7.57 | 14 | 0.5304 | 0.8475 | |
| | No log | 8.65 | 16 | 0.4964 | 0.9492 | |
| | No log | 9.73 | 18 | 0.4680 | 0.9864 | |
| | 0.6919 | 10.81 | 20 | 0.4541 | 0.9932 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.37.2 |
| - Pytorch 1.12.1 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.1 |
|
|
