cvd – AI Model by rob-jdpa | AlphaNeural AI

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rob-jdpa/
cvd

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text-classification

generated_from_trainer

meta-llama/Llama-3.2-1B

autotrain_compatible

text-generation-inference

endpoints_compatible

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cvd

This model is a fine-tuned version of meta-llama/Llama-3.2-1B on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0426
Accuracy: 0.982
Auc: 1.0

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: 0.002
train_batch_size: 3
eval_batch_size: 3
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
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Auc
7.0129	1.0	19	1.7202	0.509	0.748
1.1463	2.0	38	0.7337	0.509	1.0
0.7435	3.0	57	0.9878	0.509	0.917
1.6277	4.0	76	0.2750	0.947	0.999
1.1174	5.0	95	1.3933	0.509	0.995
0.9736	6.0	114	0.3293	0.947	1.0
0.2564	7.0	133	0.0545	1.0	1.0
0.1606	8.0	152	0.0426	0.982	1.0

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu126
Datasets 3.5.0
Tokenizers 0.21.1