---
license: other
base_model: google/mobilenet_v2_1.0_224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ai_art_exp1_mobilenet_v2
  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_mobilenet_v2

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': 0.9006666666666666}
- Loss: 0.3842
- Overall Accuracy: 0.9007
- Human Accuracy: 0.852
- Ld Accuracy: 0.984
- Sd Accuracy: 0.866

## 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 |
|:-------------:|:-----:|:----:|:-------------------:|:---------------:|:----------------:|:--------------:|:-----------:|:-----------:|
| 0.4082        | 0.992 | 93   | {'accuracy': 0.894} | 0.3844          | 0.894            | 0.8221         | 0.9847      | 0.8691      |


### Framework versions

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