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--- |
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license: other |
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base_model: google/mobilenet_v2_1.0_224 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: ai_art_exp1_mobilenet_v2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ai_art_exp1_mobilenet_v2 |
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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. |
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It achieves the following results on the evaluation set: |
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- Accuracy: {'accuracy': 0.9006666666666666} |
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- Loss: 0.3842 |
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- Overall Accuracy: 0.9007 |
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- Human Accuracy: 0.852 |
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- Ld Accuracy: 0.984 |
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- Sd Accuracy: 0.866 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | Overall Accuracy | Human Accuracy | Ld Accuracy | Sd Accuracy | |
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|:-------------:|:-----:|:----:|:-------------------:|:---------------:|:----------------:|:--------------:|:-----------:|:-----------:| |
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| 0.4082 | 0.992 | 93 | {'accuracy': 0.894} | 0.3844 | 0.894 | 0.8221 | 0.9847 | 0.8691 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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