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---
license: apache-2.0
base_model: google/efficientnet-b1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: efficientnet_b1-food101
results: []
datasets:
- food101
---
<!-- 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. -->
# efficientnet_b1-food101
This model is a fine-tuned version of [google/efficientnet-b1](https://huggingface.co/google/efficientnet-b1) on [food101](https://huggingface.co/datasets/food101) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0490
- Accuracy: 0.9947
## 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: 0.0002
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 47 | 4.3674 | 0.1548 |
| No log | 2.0 | 94 | 3.1870 | 0.8915 |
| No log | 3.0 | 141 | 0.8758 | 0.9751 |
| No log | 4.0 | 188 | 0.1010 | 0.9858 |
| No log | 5.0 | 235 | 0.0503 | 0.9893 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2 |