metadata
library_name: transformers
base_model: mo-thecreator/vit-Facial-Expression-Recognition
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-facial-expression-fatigue
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9318181818181818
vit-facial-expression-fatigue
This model is a fine-tuned version of mo-thecreator/vit-Facial-Expression-Recognition on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3637
- Accuracy: 0.9318
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2329 | 1.0 | 110 | 0.2056 | 0.9136 |
| 0.0923 | 2.0 | 220 | 0.1680 | 0.9409 |
| 0.0233 | 3.0 | 330 | 0.2320 | 0.9364 |
| 0.0084 | 4.0 | 440 | 0.2685 | 0.9409 |
| 0.002 | 5.0 | 550 | 0.3637 | 0.9318 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.10.0
- Datasets 5.0.0
- Tokenizers 0.22.2