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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- 3_class
- multi_labels
- 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: 0.2038
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 38 | 0.8817 |
| No log | 2.0 | 76 | 0.6110 |
| No log | 3.0 | 114 | 0.4243 |
| No log | 4.0 | 152 | 0.3180 |
| No log | 5.0 | 190 | 0.2811 |
| No log | 6.0 | 228 | 0.2286 |
| No log | 7.0 | 266 | 0.2133 |
| No log | 8.0 | 304 | 0.2082 |
| No log | 9.0 | 342 | 0.2050 |
| No log | 10.0 | 380 | 0.2038 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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