You can deploy this model and start earning money today!

hurtmongoose/
llama3.2-rank-1-weighted

Name: llama3.2-rank-1-weighted
Availability: InStock

peft

safetensors

generated_from_trainer

meta-llama/Llama-3.2-3B-Instruct

adapter

llama3.2

Views

No views yet

llama3.2-rank-1-weighted

This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.7097
Accuracy: 0.8983
F1: 0.8928
Recall: 0.8467
Fpr: 0.05
Auc: 0.9521
Mcc: 0.8010

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: 0.0002
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Recall	Fpr	Auc	Mcc
0.6591	1.0	313	0.3143	0.8783	0.8843	0.93	0.1733	0.9521	0.7607
0.5839	2.0	626	0.2627	0.8933	0.8971	0.93	0.1433	0.9602	0.7888
0.5069	3.0	939	0.4950	0.905	0.9009	0.8633	0.0533	0.9651	0.8128
0.3144	4.0	1252	0.5836	0.9	0.8932	0.8367	0.0367	0.9629	0.8065
0.0742	5.0	1565	0.6851	0.8933	0.8853	0.8233	0.0367	0.9648	0.7945
0.0315	6.0	1878	0.7731	0.9067	0.9004	0.8433	0.03	0.9683	0.8199
0.006	7.0	2191	0.9968	0.8933	0.8836	0.81	0.0233	0.9665	0.7978
0.0024	8.0	2504	0.9168	0.8983	0.8897	0.82	0.0233	0.9668	0.8066
0.0003	9.0	2817	0.9211	0.8967	0.8877	0.8167	0.0233	0.9665	0.8037
0.0007	10.0	3130	0.9188	0.9	0.8917	0.8233	0.0233	0.9668	0.8096

Framework versions

PEFT 0.7.0
Transformers 4.57.3
Pytorch 2.9.1+cu128
Datasets 2.15.0
Tokenizers 0.22.1

hurtmongoose/llama3.2-rank-1-weighted

llama3.2-rank-1-weighted

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hurtmongoose/
llama3.2-rank-1-weighted