metadata

library_name: transformers
license: apache-2.0
base_model: facebook/convnext-tiny-224
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: devout-voice-234
    results: []

devout-voice-234

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

Loss: 0.4823
Accuracy: 0.6195
Precision: 0.7580
Recall: 0.6195
F1: 0.6418
Roc Auc: 0.9108

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
1.3843	1.0	15	1.3708	0.2922	0.5011	0.2922	0.2957	0.6501
1.3354	2.0	30	1.3256	0.5062	0.5231	0.5062	0.4827	0.7450
1.2134	3.0	45	1.1394	0.5508	0.5749	0.5508	0.4751	0.7934
1.0408	4.0	60	0.9792	0.5188	0.6137	0.5188	0.5357	0.8100
0.881	5.0	75	0.6658	0.5508	0.5913	0.5508	0.5508	0.8320
0.7118	6.0	90	0.6165	0.5086	0.6760	0.5086	0.5172	0.8318
0.7556	7.0	105	0.5697	0.6070	0.6564	0.6070	0.6078	0.8671
0.6212	8.0	120	0.5433	0.5664	0.7000	0.5664	0.5755	0.8680
0.5591	9.0	135	0.4504	0.6797	0.7197	0.6797	0.6849	0.8983
0.4785	10.0	150	0.4269	0.6727	0.7115	0.6727	0.6706	0.9120
0.4093	11.0	165	0.4239	0.6742	0.7948	0.6742	0.6650	0.9345
0.4033	12.0	180	0.4823	0.6195	0.7580	0.6195	0.6418	0.9108

Framework versions

Transformers 4.52.3
Pytorch 2.7.0+cpu
Datasets 3.6.0
Tokenizers 0.21.0