metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-Facial-Expression-Recognition
results: []
pipeline_tag: image-classification
base_model: motheecreator/vit-Facial-Expression-Recognition
library_name: transformers
vit-Facial-Expression-Recognition
This model is a fine-tuned version of motheecreator/vit-Facial-Expression-Recognition on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3708
- Accuracy: 0.8735
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: 3e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5551 | 0.4327 | 100 | 0.3728 | 0.8742 |
| 0.5725 | 0.8653 | 200 | 0.3702 | 0.8749 |
| 0.5513 | 1.2980 | 300 | 0.3683 | 0.8751 |
| 0.5565 | 1.7307 | 400 | 0.3681 | 0.8754 |
| 0.5395 | 2.1633 | 500 | 0.3708 | 0.8735 |
| 0.5306 | 2.5960 | 600 | 0.3696 | 0.8738 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1