metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013CKPlus
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
args: default
metrics:
- name: Accuracy
type: accuracy
value: 1
beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013CKPlus
This model is a fine-tuned version of Celal11/beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013 on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0089
- Accuracy: 1.0
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.9918 | 0.97 | 27 | 0.2528 | 0.8985 |
0.3355 | 1.97 | 54 | 0.0703 | 0.9797 |
0.2484 | 2.97 | 81 | 0.0232 | 0.9848 |
0.1971 | 3.97 | 108 | 0.0197 | 0.9848 |
0.1731 | 4.97 | 135 | 0.0089 | 1.0 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1