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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: doodle_mobilenet |
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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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# doodle_mobilenet |
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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 the |
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[Quick, Draw! small dataset](https://huggingface.co/datasets/Xenova/quickdraw-small) |
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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: 0.0008 |
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- train_batch_size: 512 |
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- eval_batch_size: 512 |
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- seed: 42 |
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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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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:-----:|:---------------:|:--------:| |
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| 1.4546 | 0.5688 | 5000 | 1.4383 | 0.6474 | |
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| 1.3759 | 1.1377 | 10000 | 1.3850 | 0.6610 | |
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| 1.3508 | 1.7065 | 15000 | 1.3163 | 0.6737 | |
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| 1.294 | 2.2753 | 20000 | 1.2832 | 0.6829 | |
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| 1.2811 | 2.8441 | 25000 | 1.2581 | 0.6881 | |
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| 1.2331 | 3.4130 | 30000 | 1.2387 | 0.6926 | |
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| 1.2276 | 3.9818 | 35000 | 1.2227 | 0.6978 | |
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| 1.1964 | 4.5506 | 40000 | 1.2196 | 0.6990 | |
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| 1.1498 | 5.1195 | 45000 | 1.1994 | 0.7036 | |
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| 1.1548 | 5.6883 | 50000 | 1.1900 | 0.7052 | |
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| 1.1232 | 6.2571 | 55000 | 1.1831 | 0.7075 | |
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| 1.1264 | 6.8259 | 60000 | 1.1695 | 0.7100 | |
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| 1.0896 | 7.3948 | 65000 | 1.1584 | 0.7128 | |
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| 1.0917 | 7.9636 | 70000 | 1.1535 | 0.7155 | |
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| 1.0654 | 8.5324 | 75000 | 1.1545 | 0.7144 | |
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| 1.0395 | 9.1013 | 80000 | 1.1471 | 0.7169 | |
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| 1.0383 | 9.6701 | 85000 | 1.1722 | 0.7136 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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