metadata

library_name: transformers
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: cool-darkness-225
    results: []

cool-darkness-225

This model is a fine-tuned version of facebook/convnextv2-tiny-1k-224 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0830
Accuracy: 0.9783
Precision: 0.9787
Recall: 0.9783
F1: 0.9783
Roc Auc: 0.9995

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: 0.0001
train_batch_size: 256
eval_batch_size: 256
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: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 40

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Roc Auc
1.7349	1.0	161	0.7668	0.8664	0.8687	0.8664	0.8658	0.9880
0.6429	2.0	322	0.2021	0.9498	0.9506	0.9498	0.9498	0.9979
0.4363	3.0	483	0.1325	0.9601	0.9606	0.9601	0.9600	0.9991
0.3774	4.0	644	0.1117	0.966	0.9667	0.966	0.9660	0.9992
0.3413	5.0	805	0.0979	0.9694	0.9697	0.9694	0.9693	0.9994
0.3051	6.0	966	0.0824	0.9748	0.9749	0.9748	0.9748	0.9995
0.2808	7.0	1127	0.0796	0.9742	0.9744	0.9742	0.9742	0.9995
0.2622	8.0	1288	0.0753	0.9764	0.9765	0.9764	0.9765	0.9995
0.2512	9.0	1449	0.0769	0.9748	0.9748	0.9748	0.9747	0.9996
0.2368	10.0	1610	0.0816	0.9777	0.9780	0.9777	0.9777	0.9995
0.2303	11.0	1771	0.0686	0.98	0.9800	0.98	0.9800	0.9996
0.2141	12.0	1932	0.0684	0.9791	0.9792	0.9791	0.9791	0.9996
0.2086	13.0	2093	0.0766	0.9782	0.9787	0.9782	0.9783	0.9996
0.2012	14.0	2254	0.0830	0.9783	0.9787	0.9783	0.9783	0.9995

Framework versions

Transformers 4.52.3
Pytorch 2.7.0+cpu
Datasets 3.6.0
Tokenizers 0.21.0