ViT_face / README.md
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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- HHD
- 3_class
- ViT
- generated_from_trainer
model-index:
- name: ViT_face
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. -->
# ViT_face
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 face dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6941
## 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: 2e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 10 | 1.0691 |
| No log | 2.0 | 20 | 1.0378 |
| No log | 3.0 | 30 | 0.9958 |
| No log | 4.0 | 40 | 0.9437 |
| No log | 5.0 | 50 | 0.8915 |
| No log | 6.0 | 60 | 0.8396 |
| No log | 7.0 | 70 | 0.7950 |
| No log | 8.0 | 80 | 0.7602 |
| No log | 9.0 | 90 | 0.7246 |
| No log | 10.0 | 100 | 0.7009 |
| No log | 11.0 | 110 | 0.6882 |
| No log | 12.0 | 120 | 0.6700 |
| No log | 13.0 | 130 | 0.6629 |
| No log | 14.0 | 140 | 0.6646 |
| No log | 15.0 | 150 | 0.6558 |
| No log | 16.0 | 160 | 0.6679 |
| No log | 17.0 | 170 | 0.6637 |
| No log | 18.0 | 180 | 0.6689 |
| No log | 19.0 | 190 | 0.6690 |
| No log | 20.0 | 200 | 0.6744 |
| No log | 21.0 | 210 | 0.6787 |
| No log | 22.0 | 220 | 0.6823 |
| No log | 23.0 | 230 | 0.6832 |
| No log | 24.0 | 240 | 0.6866 |
| No log | 25.0 | 250 | 0.6883 |
| No log | 26.0 | 260 | 0.6912 |
| No log | 27.0 | 270 | 0.6923 |
| No log | 28.0 | 280 | 0.6935 |
| No log | 29.0 | 290 | 0.6939 |
| No log | 30.0 | 300 | 0.6941 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1