grateful-shape-212 – AI Model by BeckerAnas | AlphaNeural AI

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BeckerAnas/
grateful-shape-212

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image-classification

generated_from_trainer

facebook/convnextv2-tiny-1k-224

autotrain_compatible

endpoints_compatible

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grateful-shape-212

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: 1.3777
Accuracy: 0.2708
Precision: 0.4203
Recall: 0.2708
F1: 0.3127
Roc Auc: 0.5428

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Roc Auc
1.4367	1.0	17	1.3810	0.0898	0.4478	0.0898	0.1092	0.5060
1.3894	2.0	34	1.3751	0.1823	0.4052	0.1823	0.2266	0.5250
1.3619	3.0	51	1.3766	0.2422	0.4100	0.2422	0.2876	0.5369
1.3523	4.0	68	1.3776	0.2708	0.4238	0.2708	0.3132	0.5422
1.3475	5.0	85	1.3777	0.2708	0.4203	0.2708	0.3127	0.5428

Framework versions

Transformers 4.52.3
Pytorch 2.7.0+cpu
Datasets 3.6.0
Tokenizers 0.21.0