This model is a fine-tuned version of timm/convnext_tiny.in12k_ft_in1k on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0569
Accuracy: 0.9826

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: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
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
lr_scheduler_warmup_steps: 235
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4734	1.0	196	0.1143	0.9651
0.3522	2.0	392	0.0793	0.9732
0.2655	3.0	588	0.0569	0.9826

Framework versions

Transformers 5.5.0
Pytorch 2.11.0+cu128
Datasets 4.8.4
Tokenizers 0.22.2

Taozhiyaoyao1/convnext_tiny.in12k_ft_in1k-finetuned-cifar10

convnext_tiny.in12k_ft_in1k-finetuned-cifar10

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Taozhiyaoyao1/
convnext_tiny.in12k_ft_in1k-finetuned-cifar10