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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224 |
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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: Human-Action-Recognition-VIT-Base-patch16-224 |
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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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# Human-Action-Recognition-VIT-Base-patch16-224 |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4005 |
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- Accuracy: 0.8786 |
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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: 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 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 2.6396 | 0.99 | 39 | 2.0436 | 0.4425 | |
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| 1.4579 | 2.0 | 79 | 0.7553 | 0.7917 | |
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| 0.8342 | 2.99 | 118 | 0.5296 | 0.8417 | |
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| 0.6649 | 4.0 | 158 | 0.4978 | 0.8496 | |
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| 0.6137 | 4.99 | 197 | 0.4460 | 0.8595 | |
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| 0.5374 | 6.0 | 237 | 0.4356 | 0.8627 | |
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| 0.514 | 6.99 | 276 | 0.4349 | 0.8615 | |
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| 0.475 | 8.0 | 316 | 0.4005 | 0.8786 | |
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| 0.4663 | 8.99 | 355 | 0.4164 | 0.8659 | |
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| 0.4178 | 10.0 | 395 | 0.4128 | 0.8738 | |
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| 0.4226 | 10.99 | 434 | 0.4115 | 0.8690 | |
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| 0.3896 | 12.0 | 474 | 0.4112 | 0.875 | |
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| 0.3866 | 12.99 | 513 | 0.4072 | 0.8714 | |
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| 0.3632 | 14.0 | 553 | 0.4106 | 0.8718 | |
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| 0.3596 | 14.99 | 592 | 0.4043 | 0.8714 | |
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| 0.3421 | 16.0 | 632 | 0.4128 | 0.8675 | |
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| 0.344 | 16.99 | 671 | 0.4181 | 0.8643 | |
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| 0.3447 | 18.0 | 711 | 0.4128 | 0.8687 | |
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| 0.3407 | 18.99 | 750 | 0.4097 | 0.8714 | |
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| 0.3267 | 19.75 | 780 | 0.4097 | 0.8683 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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