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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: face_predict |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train[:800] |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5625 |
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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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# face_predict |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2322 |
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- Accuracy: 0.5625 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 6 |
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- total_train_batch_size: 192 |
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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: 40 |
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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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| No log | 0.9 | 3 | 2.0747 | 0.1187 | |
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| No log | 1.8 | 6 | 2.0728 | 0.1375 | |
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| 2.0713 | 3.0 | 10 | 2.0449 | 0.2 | |
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| 2.0713 | 3.9 | 13 | 2.0225 | 0.2562 | |
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| 2.0713 | 4.8 | 16 | 1.9779 | 0.2938 | |
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| 1.9642 | 6.0 | 20 | 1.8985 | 0.3688 | |
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| 1.9642 | 6.9 | 23 | 1.8440 | 0.4188 | |
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| 1.9642 | 7.8 | 26 | 1.7593 | 0.4437 | |
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| 1.7442 | 9.0 | 30 | 1.6551 | 0.4875 | |
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| 1.7442 | 9.9 | 33 | 1.5996 | 0.4875 | |
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| 1.7442 | 10.8 | 36 | 1.5324 | 0.5188 | |
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| 1.5402 | 12.0 | 40 | 1.5053 | 0.525 | |
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| 1.5402 | 12.9 | 43 | 1.4543 | 0.5188 | |
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| 1.5402 | 13.8 | 46 | 1.4335 | 0.5188 | |
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| 1.4064 | 15.0 | 50 | 1.3768 | 0.5938 | |
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| 1.4064 | 15.9 | 53 | 1.3583 | 0.6 | |
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| 1.4064 | 16.8 | 56 | 1.3464 | 0.575 | |
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| 1.2844 | 18.0 | 60 | 1.3245 | 0.6125 | |
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| 1.2844 | 18.9 | 63 | 1.3265 | 0.5563 | |
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| 1.2844 | 19.8 | 66 | 1.2899 | 0.5813 | |
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| 1.1834 | 21.0 | 70 | 1.2863 | 0.5625 | |
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| 1.1834 | 21.9 | 73 | 1.2939 | 0.5687 | |
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| 1.1834 | 22.8 | 76 | 1.2508 | 0.5938 | |
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| 1.1046 | 24.0 | 80 | 1.2604 | 0.5563 | |
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| 1.1046 | 24.9 | 83 | 1.2344 | 0.6062 | |
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| 1.1046 | 25.8 | 86 | 1.2124 | 0.6125 | |
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| 1.0379 | 27.0 | 90 | 1.2053 | 0.6312 | |
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| 1.0379 | 27.9 | 93 | 1.3067 | 0.5375 | |
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| 1.0379 | 28.8 | 96 | 1.2247 | 0.5875 | |
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| 1.0064 | 30.0 | 100 | 1.2060 | 0.625 | |
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| 1.0064 | 30.9 | 103 | 1.2308 | 0.575 | |
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| 1.0064 | 31.8 | 106 | 1.1936 | 0.6188 | |
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| 0.9611 | 33.0 | 110 | 1.2257 | 0.5938 | |
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| 0.9611 | 33.9 | 113 | 1.2302 | 0.5563 | |
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| 0.9611 | 34.8 | 116 | 1.2172 | 0.6 | |
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| 0.9351 | 36.0 | 120 | 1.2355 | 0.55 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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