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--- |
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license: apache-2.0 |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: google-vit-base-patch16-224-cartoon-face-recognition |
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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 |
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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: 0.9004629629629629 |
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- name: Precision |
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type: precision |
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value: 0.9066341895316832 |
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- name: Recall |
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type: recall |
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value: 0.9004629629629629 |
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- name: F1 |
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type: f1 |
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value: 0.8984296743444529 |
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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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# google-vit-base-patch16-224-cartoon-face-recognition |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3707 |
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- Accuracy: 0.9005 |
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- Precision: 0.9066 |
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- Recall: 0.9005 |
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- F1: 0.8984 |
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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: 0.00012 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 0.89 | 6 | 0.5459 | 0.8611 | 0.8683 | 0.8611 | 0.8577 | |
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| 0.0812 | 1.89 | 12 | 0.4703 | 0.8796 | 0.8833 | 0.8796 | 0.8764 | |
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| 0.0812 | 2.89 | 18 | 0.4430 | 0.8935 | 0.8969 | 0.8935 | 0.8906 | |
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| 0.0307 | 3.89 | 24 | 0.4045 | 0.8819 | 0.8849 | 0.8819 | 0.8767 | |
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| 0.0091 | 4.89 | 30 | 0.3672 | 0.9005 | 0.9025 | 0.9005 | 0.8980 | |
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| 0.0091 | 5.89 | 36 | 0.3841 | 0.9028 | 0.9125 | 0.9028 | 0.9011 | |
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| 0.0043 | 6.89 | 42 | 0.3926 | 0.9005 | 0.9073 | 0.9005 | 0.8972 | |
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| 0.0043 | 7.89 | 48 | 0.3786 | 0.8958 | 0.9005 | 0.8958 | 0.8931 | |
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| 0.0031 | 8.89 | 54 | 0.3791 | 0.9028 | 0.9091 | 0.9028 | 0.9007 | |
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| 0.002 | 9.89 | 60 | 0.3677 | 0.9028 | 0.9106 | 0.9028 | 0.9001 | |
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| 0.002 | 10.89 | 66 | 0.3740 | 0.9028 | 0.9099 | 0.9028 | 0.9007 | |
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| 0.0027 | 11.89 | 72 | 0.3869 | 0.8981 | 0.9043 | 0.8981 | 0.8956 | |
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| 0.0027 | 12.89 | 78 | 0.3801 | 0.8981 | 0.9021 | 0.8981 | 0.8954 | |
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| 0.004 | 13.89 | 84 | 0.3674 | 0.9051 | 0.9113 | 0.9051 | 0.9028 | |
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| 0.0024 | 14.89 | 90 | 0.3620 | 0.9051 | 0.9096 | 0.9051 | 0.9027 | |
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| 0.0024 | 15.89 | 96 | 0.3670 | 0.9028 | 0.9089 | 0.9028 | 0.9006 | |
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| 0.0021 | 16.89 | 102 | 0.3827 | 0.9005 | 0.9065 | 0.9005 | 0.8980 | |
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| 0.0021 | 17.89 | 108 | 0.3748 | 0.8981 | 0.9049 | 0.8981 | 0.8958 | |
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| 0.0022 | 18.89 | 114 | 0.3825 | 0.9028 | 0.9101 | 0.9028 | 0.9006 | |
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| 0.0019 | 19.89 | 120 | 0.3707 | 0.9005 | 0.9066 | 0.9005 | 0.8984 | |
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### Framework versions |
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- Transformers 4.24.0.dev0 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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