metadata
tags:
- generated_from_trainer
datasets:
- food101
model-index:
- name: food-image-classification
results: []
food-image-classification
This model was trained from scratch on the food101 dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.3752
- eval_accuracy: 0.9038
- eval_runtime: 155.8581
- eval_samples_per_second: 97.204
- eval_steps_per_second: 6.076
- epoch: 39.07
- step: 37000
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 500
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1