lora_model_results

ArjunWK/lora_model_results

lora_model_results is a machine learning model from ArjunWK. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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Hugging Face

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At a glance

Library: peft
License: apache-2.0
Access: Public
Created: Dec 6, 2025
Updated: Dec 6, 2025
SHA: 3f454b06

Base models

Model card

From the Hugging Face model README

lora_model_results

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4577
Accuracy: 0.897
F1: 0.8963
Precision: 0.9026
Recall: 0.89

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: 0.001
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	125	0.3026	0.883	0.8770	0.9246	0.834
No log	2.0	250	0.4670	0.858	0.8422	0.9475	0.758
No log	3.0	375	0.3810	0.9	0.8975	0.9202	0.876
0.2543	4.0	500	0.4339	0.899	0.8985	0.9030	0.894
0.2543	5.0	625	0.4577	0.897	0.8963	0.9026	0.89

Framework versions

PEFT 0.18.0
Transformers 4.57.2
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1

Library: peft
License: apache-2.0
Created: Dec 6, 2025
Updated: Dec 6, 2025