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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: Action_model |
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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: 0.7666666666666667 |
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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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# Action_model |
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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: 1.0234 |
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- Accuracy: 0.7667 |
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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: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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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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| 0.4299 | 0.32 | 100 | 0.7981 | 0.7457 | |
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| 0.3903 | 0.64 | 200 | 0.7173 | 0.7771 | |
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| 0.4296 | 0.96 | 300 | 0.6869 | 0.7876 | |
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| 0.3589 | 1.27 | 400 | 0.9108 | 0.7314 | |
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| 0.3007 | 1.59 | 500 | 0.9720 | 0.7133 | |
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| 0.2817 | 1.91 | 600 | 0.8504 | 0.7486 | |
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| 0.2754 | 2.23 | 700 | 0.9009 | 0.7410 | |
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| 0.2226 | 2.55 | 800 | 0.9020 | 0.7495 | |
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| 0.285 | 2.87 | 900 | 1.0012 | 0.7295 | |
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| 0.2307 | 3.18 | 1000 | 0.8204 | 0.7810 | |
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| 0.2398 | 3.5 | 1100 | 0.8857 | 0.7695 | |
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| 0.1948 | 3.82 | 1200 | 0.9110 | 0.7571 | |
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| 0.1962 | 4.14 | 1300 | 0.9775 | 0.7533 | |
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| 0.2159 | 4.46 | 1400 | 0.9719 | 0.7457 | |
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| 0.1361 | 4.78 | 1500 | 0.9262 | 0.7571 | |
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| 0.1898 | 5.1 | 1600 | 0.9130 | 0.7705 | |
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| 0.1153 | 5.41 | 1700 | 1.0409 | 0.7438 | |
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| 0.1489 | 5.73 | 1800 | 1.0176 | 0.7495 | |
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| 0.1515 | 6.05 | 1900 | 1.0507 | 0.7486 | |
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| 0.1126 | 6.37 | 2000 | 1.1423 | 0.7210 | |
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| 0.1319 | 6.69 | 2100 | 1.1008 | 0.7467 | |
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| 0.1424 | 7.01 | 2200 | 1.0798 | 0.7419 | |
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| 0.0955 | 7.32 | 2300 | 1.0767 | 0.7505 | |
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| 0.1077 | 7.64 | 2400 | 1.0920 | 0.7457 | |
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| 0.1048 | 7.96 | 2500 | 1.0040 | 0.7733 | |
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| 0.0965 | 8.28 | 2600 | 1.0384 | 0.7610 | |
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| 0.0995 | 8.6 | 2700 | 1.0423 | 0.7648 | |
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| 0.1213 | 8.92 | 2800 | 1.0544 | 0.7619 | |
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| 0.0863 | 9.24 | 2900 | 1.0454 | 0.7629 | |
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| 0.0926 | 9.55 | 3000 | 1.0380 | 0.7676 | |
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| 0.0536 | 9.87 | 3100 | 1.0234 | 0.7667 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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