metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: 13E-affecthq-fer-balanced
    results: []
datasets:
  - Piro17/balancednumber-affecthqnet-fer2013

13E-affecthq-fer-balanced

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on Piro17/balancednumber-affecthqnet-fer2013 dataset. It achieves the following results on the evaluation set:

Loss: 1.0526
Accuracy: 0.6225
Precision: 0.6161
Recall: 0.6225
F1: 0.6167

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: 13

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.7863	1.0	133	1.7632	0.4005	0.3617	0.4005	0.3058
1.3653	2.0	266	1.3630	0.5049	0.4838	0.5049	0.4445
1.2468	3.0	399	1.2475	0.5466	0.5451	0.5466	0.5115
1.1527	4.0	532	1.1865	0.5761	0.5612	0.5761	0.5580
1.0862	5.0	665	1.1448	0.5785	0.5687	0.5785	0.5659
1.064	6.0	798	1.1108	0.5972	0.5867	0.5972	0.5853
1.0037	7.0	931	1.0969	0.6019	0.5968	0.6019	0.5946
0.9533	8.0	1064	1.0764	0.6126	0.6034	0.6126	0.6046
0.9063	9.0	1197	1.0711	0.6155	0.6035	0.6155	0.6047
0.8666	10.0	1330	1.0589	0.6173	0.6107	0.6173	0.6108
0.8364	11.0	1463	1.0556	0.6178	0.6110	0.6178	0.6108
0.8659	12.0	1596	1.0521	0.6197	0.6141	0.6197	0.6151
0.8383	13.0	1729	1.0526	0.6225	0.6161	0.6225	0.6167

Framework versions

Transformers 4.27.0.dev0
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2