---
license: other
base_model: google/mobilenet_v2_1.0_224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ai_art_exp3_mobilenetv2
  results: []
---

<!-- 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. -->

# ai_art_exp3_mobilenetv2

This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Accuracy: {'accuracy': 0.65}
- Loss: 0.8813
- Overall Accuracy: 0.65
- Human Accuracy: 0.34
- Ld Accuracy: 0.84
- Sd Accuracy: 0.77

## 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 |
|:-------------:|:-----:|:----:|:--------------------------------:|:---------------:|:----------------:|:--------------:|:-----------:|:-----------:|
| 1.0707        | 0.96  | 18   | {'accuracy': 0.6333333333333333} | 0.8947          | 0.6333           | 0.3426         | 0.8485      | 0.7419      |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1