metadata
library_name: transformers
base_model: motheecreator/vit-Facial-Expression-Recognition
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: FER-Facial-Expression-Recognition
results: []
FER-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: 0.4710
- Accuracy: 0.8474
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.8868 | 0.8959 | 100 | 1.7638 | 0.5923 |
| 1.2277 | 1.7962 | 200 | 1.1092 | 0.7253 |
| 0.8414 | 2.6965 | 300 | 0.8105 | 0.8041 |
| 0.7076 | 3.5969 | 400 | 0.6746 | 0.8256 |
| 0.6079 | 4.4972 | 500 | 0.6111 | 0.8287 |
| 0.5624 | 5.3975 | 600 | 0.5529 | 0.8379 |
| 0.5254 | 6.2979 | 700 | 0.5266 | 0.8399 |
| 0.4784 | 7.1982 | 800 | 0.4978 | 0.8433 |
| 0.4634 | 8.0985 | 900 | 0.4844 | 0.8458 |
| 0.4305 | 8.9944 | 1000 | 0.4710 | 0.8474 |
| 0.3995 | 9.8947 | 1100 | 0.4381 | 0.8564 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3