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Human-Action-Recognition-VIT-Base-patch16-224
wendyLIUyejia/Human-Action-Recognition-VIT-Base-patch16-224
Human-Action-Recognition-VIT-Base-patch16-224 is a image classification model from wendyLIUyejia. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Oct 29, 2024
- Updated
- Oct 29, 2024
- SHA
- 0272d1a6
Base models
Model card
From the Hugging Face model README
<!-- 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 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4165
- Accuracy: 0.8782
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 |
|---|---|---|---|---|
| 2.6245 | 0.9873 | 39 | 2.0901 | 0.4429 |
| 1.4804 | 2.0 | 79 | 0.7998 | 0.7841 |
| 0.8447 | 2.9873 | 118 | 0.5635 | 0.8345 |
| 0.6764 | 4.0 | 158 | 0.4952 | 0.8476 |
| 0.6202 | 4.9873 | 197 | 0.4849 | 0.8595 |
| 0.5627 | 6.0 | 237 | 0.4604 | 0.8643 |
| 0.5219 | 6.9873 | 276 | 0.4567 | 0.8663 |
| 0.4912 | 8.0 | 316 | 0.4371 | 0.8718 |
| 0.4736 | 8.9873 | 355 | 0.4320 | 0.8671 |
| 0.4347 | 10.0 | 395 | 0.4229 | 0.8746 |
| 0.4274 | 10.9873 | 434 | 0.4211 | 0.8734 |
| 0.4011 | 12.0 | 474 | 0.4234 | 0.8762 |
| 0.3845 | 12.9873 | 513 | 0.4247 | 0.8742 |
| 0.3797 | 14.0 | 553 | 0.4193 | 0.8746 |
| 0.374 | 14.9873 | 592 | 0.4204 | 0.8766 |
| 0.3567 | 16.0 | 632 | 0.4165 | 0.8782 |
| 0.3565 | 16.9873 | 671 | 0.4212 | 0.8742 |
| 0.3375 | 18.0 | 711 | 0.4241 | 0.875 |
| 0.3366 | 18.9873 | 750 | 0.4221 | 0.875 |
| 0.3338 | 19.7468 | 780 | 0.4215 | 0.8766 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Oct 29, 2024
- Updated
- Oct 29, 2024