dafa-w/emotion_classification

results

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: 1.5254
• Accuracy: 0.4313

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: 0.001
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• 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: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	40	1.9225	0.25
No log	2.0	80	1.5751	0.4188
No log	3.0	120	1.5159	0.3875
No log	4.0	160	1.5254	0.4313
1.2986	5.0	200	1.6747	0.4125
1.2986	6.0	240	1.8746	0.3563
1.2986	7.0	280	2.1805	0.35
1.2986	8.0	320	2.3406	0.3125
1.2986	9.0	360	2.3001	0.3438
0.7028	10.0	400	2.2428	0.2625

Framework versions

• Transformers 4.50.3
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1