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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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- image-classification |
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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: action_class |
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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: 0.8576449912126538 |
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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 action_class dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4589 |
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- Accuracy: 0.8576 |
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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: 16 |
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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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| 1.2754 | 0.37 | 100 | 1.1163 | 0.7329 | |
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| 0.9345 | 0.75 | 200 | 0.8296 | 0.7996 | |
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| 0.8816 | 1.12 | 300 | 0.7156 | 0.8102 | |
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| 0.7425 | 1.49 | 400 | 0.6529 | 0.8067 | |
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| 0.6883 | 1.87 | 500 | 0.6079 | 0.8243 | |
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| 0.5454 | 2.24 | 600 | 0.5605 | 0.8348 | |
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| 0.5383 | 2.61 | 700 | 0.5571 | 0.8295 | |
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| 0.5442 | 2.99 | 800 | 0.5864 | 0.8190 | |
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| 0.3986 | 3.36 | 900 | 0.5632 | 0.8313 | |
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| 0.3438 | 3.73 | 1000 | 0.5606 | 0.8366 | |
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| 0.4345 | 4.1 | 1100 | 0.5354 | 0.8366 | |
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| 0.4523 | 4.48 | 1200 | 0.4988 | 0.8576 | |
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| 0.3162 | 4.85 | 1300 | 0.5099 | 0.8541 | |
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| 0.3793 | 5.22 | 1400 | 0.5190 | 0.8436 | |
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| 0.3228 | 5.6 | 1500 | 0.4589 | 0.8576 | |
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| 0.1795 | 5.97 | 1600 | 0.5096 | 0.8489 | |
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| 0.2626 | 6.34 | 1700 | 0.5403 | 0.8489 | |
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| 0.3041 | 6.72 | 1800 | 0.4908 | 0.8489 | |
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| 0.1831 | 7.09 | 1900 | 0.5721 | 0.8383 | |
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| 0.2275 | 7.46 | 2000 | 0.5349 | 0.8313 | |
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| 0.1762 | 7.84 | 2100 | 0.5204 | 0.8541 | |
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| 0.2112 | 8.21 | 2200 | 0.5189 | 0.8629 | |
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| 0.1242 | 8.58 | 2300 | 0.5377 | 0.8471 | |
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| 0.1207 | 8.96 | 2400 | 0.5325 | 0.8559 | |
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| 0.1806 | 9.33 | 2500 | 0.5150 | 0.8647 | |
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| 0.1793 | 9.7 | 2600 | 0.5153 | 0.8664 | |
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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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