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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
|