tags: | |
- generated_from_trainer | |
metrics: | |
- accuracy | |
model-index: | |
- name: swin-food102 | |
results: [] | |
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# swin-food102 | |
This model is a fine-tuned version of [juliensimon/autotrain-food101-1471154053](https://huggingface.co/juliensimon/autotrain-food101-1471154053) on the None dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.2510 | |
- Accuracy: 0.9338 | |
## 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: 1e-05 | |
- train_batch_size: 16 | |
- eval_batch_size: 64 | |
- seed: 42 | |
- gradient_accumulation_steps: 8 | |
- total_train_batch_size: 128 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- num_epochs: 3 | |
- mixed_precision_training: Native AMP | |
### Training results | |
| Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
|:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| 1.1648 | 1.0 | 597 | 0.3118 | 0.9218 | | |
| 0.31 | 2.0 | 1194 | 0.2606 | 0.9322 | | |
| 0.2488 | 3.0 | 1791 | 0.2510 | 0.9338 | | |
### Framework versions | |
- Transformers 4.23.1 | |
- Pytorch 1.12.1+cu102 | |
- Datasets 2.4.0 | |
- Tokenizers 0.13.1 | |