---
license: apache-2.0
base_model: google/efficientnet-b3
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ai_art_exp1_efficientnetb3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ai_art_exp1_efficientnetb3

This model is a fine-tuned version of [google/efficientnet-b3](https://huggingface.co/google/efficientnet-b3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Accuracy: {'accuracy': 0.86}
- Loss: 0.5031
- Overall Accuracy: 0.86
- Human Accuracy: 0.688
- Ld Accuracy: 0.996
- Sd Accuracy: 0.896

## 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: 1

### Training results

| Training Loss | Epoch | Step | Accuracy            | Validation Loss | Overall Accuracy | Human Accuracy | Ld Accuracy | Sd Accuracy |
|:-------------:|:-----:|:----:|:-------------------:|:---------------:|:----------------:|:--------------:|:-----------:|:-----------:|
| 0.5418        | 0.992 | 93   | {'accuracy': 0.868} | 0.5072          | 0.868            | 0.7280         | 0.9923      | 0.8753      |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1