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--- |
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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: resnet-50 |
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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: 0.5408191696851491 |
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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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# resnet-50 |
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This model was trained from scratch on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1947 |
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- Accuracy: 0.5408 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 10 |
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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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| 1.5588 | 1.0 | 252 | 1.4406 | 0.4558 | |
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| 1.4831 | 2.0 | 505 | 1.3683 | 0.4790 | |
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| 1.4776 | 3.0 | 757 | 1.3199 | 0.4937 | |
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| 1.4246 | 4.0 | 1010 | 1.2881 | 0.5068 | |
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| 1.4102 | 5.0 | 1262 | 1.2469 | 0.5247 | |
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| 1.3806 | 6.0 | 1515 | 1.2276 | 0.5258 | |
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| 1.3861 | 7.0 | 1767 | 1.2121 | 0.5411 | |
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| 1.3791 | 8.0 | 2020 | 1.2075 | 0.5433 | |
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| 1.3683 | 9.0 | 2272 | 1.2011 | 0.5422 | |
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| 1.4119 | 9.98 | 2520 | 1.1947 | 0.5408 | |
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### Framework versions |
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- Transformers 4.30.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.13.3 |
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