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---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Human-Action-Recognition-VIT-Base-patch16-224
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Human-Action-Recognition-VIT-Base-patch16-224
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.
It achieves the following results on the evaluation set:
- Loss: 0.4005
- Accuracy: 0.8786
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.6396 | 0.99 | 39 | 2.0436 | 0.4425 |
| 1.4579 | 2.0 | 79 | 0.7553 | 0.7917 |
| 0.8342 | 2.99 | 118 | 0.5296 | 0.8417 |
| 0.6649 | 4.0 | 158 | 0.4978 | 0.8496 |
| 0.6137 | 4.99 | 197 | 0.4460 | 0.8595 |
| 0.5374 | 6.0 | 237 | 0.4356 | 0.8627 |
| 0.514 | 6.99 | 276 | 0.4349 | 0.8615 |
| 0.475 | 8.0 | 316 | 0.4005 | 0.8786 |
| 0.4663 | 8.99 | 355 | 0.4164 | 0.8659 |
| 0.4178 | 10.0 | 395 | 0.4128 | 0.8738 |
| 0.4226 | 10.99 | 434 | 0.4115 | 0.8690 |
| 0.3896 | 12.0 | 474 | 0.4112 | 0.875 |
| 0.3866 | 12.99 | 513 | 0.4072 | 0.8714 |
| 0.3632 | 14.0 | 553 | 0.4106 | 0.8718 |
| 0.3596 | 14.99 | 592 | 0.4043 | 0.8714 |
| 0.3421 | 16.0 | 632 | 0.4128 | 0.8675 |
| 0.344 | 16.99 | 671 | 0.4181 | 0.8643 |
| 0.3447 | 18.0 | 711 | 0.4128 | 0.8687 |
| 0.3407 | 18.99 | 750 | 0.4097 | 0.8714 |
| 0.3267 | 19.75 | 780 | 0.4097 | 0.8683 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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