hq_fer2013notestaugM
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.8297
- Accuracy: 0.6998
- Precision: 0.7022
- Recall: 0.6998
- F1: 0.6999
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 17
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
1.2858 | 1.0 | 353 | 1.2814 | 0.5545 | 0.5432 | 0.5545 | 0.5122 |
1.0247 | 2.0 | 706 | 1.0343 | 0.6288 | 0.6235 | 0.6288 | 0.6136 |
0.9403 | 3.0 | 1059 | 0.9500 | 0.6607 | 0.6592 | 0.6607 | 0.6522 |
0.8501 | 4.0 | 1412 | 0.8971 | 0.6803 | 0.6761 | 0.6803 | 0.6760 |
0.8148 | 5.0 | 1765 | 0.8733 | 0.6857 | 0.6881 | 0.6857 | 0.6854 |
0.7898 | 6.0 | 2118 | 0.8526 | 0.6913 | 0.6911 | 0.6913 | 0.6888 |
0.7074 | 7.0 | 2471 | 0.8408 | 0.6959 | 0.6971 | 0.6959 | 0.6953 |
0.7273 | 8.0 | 2824 | 0.8361 | 0.6980 | 0.6971 | 0.6980 | 0.6949 |
0.6982 | 9.0 | 3177 | 0.8297 | 0.6998 | 0.7022 | 0.6998 | 0.6999 |
0.6994 | 10.0 | 3530 | 0.8287 | 0.6998 | 0.7002 | 0.6998 | 0.6991 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
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Evaluation results
- Accuracy on imagefolderself-reported0.700
- Precision on imagefolderself-reported0.702
- Recall on imagefolderself-reported0.700
- F1 on imagefolderself-reported0.700