| | --- |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - imagefolder |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: resnet-50 |
| | 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: 0.5408191696851491 |
| | --- |
| | |
| | <!-- 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 |
| |
|
| | This model was trained from scratch on the imagefolder dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.1947 |
| | - Accuracy: 0.5408 |
| |
|
| | ## 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: 32 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 128 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 1.5588 | 1.0 | 252 | 1.4406 | 0.4558 | |
| | | 1.4831 | 2.0 | 505 | 1.3683 | 0.4790 | |
| | | 1.4776 | 3.0 | 757 | 1.3199 | 0.4937 | |
| | | 1.4246 | 4.0 | 1010 | 1.2881 | 0.5068 | |
| | | 1.4102 | 5.0 | 1262 | 1.2469 | 0.5247 | |
| | | 1.3806 | 6.0 | 1515 | 1.2276 | 0.5258 | |
| | | 1.3861 | 7.0 | 1767 | 1.2121 | 0.5411 | |
| | | 1.3791 | 8.0 | 2020 | 1.2075 | 0.5433 | |
| | | 1.3683 | 9.0 | 2272 | 1.2011 | 0.5422 | |
| | | 1.4119 | 9.98 | 2520 | 1.1947 | 0.5408 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.30.0 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.14.6 |
| | - Tokenizers 0.13.3 |
| |
|
