distilbert-base-uncased-lora-text-classification

whoshubham/distilbert-base-uncased-lora-text-classification

distilbert-base-uncased-lora-text-classification is a machine learning model from whoshubham. 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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At a glance

Library: peft
License: apache-2.0
Access: Public
Created: Sep 18, 2024
Updated: Sep 18, 2024
SHA: 9332ea33

Base models

Model card

From the Hugging Face model README

distilbert-base-uncased-lora-text-classification

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: 0.2504
Accuracy: {'accuracy': 0.903}

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: 50
eval_batch_size: 50
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	20	0.3354	{'accuracy': 0.884}
No log	2.0	40	0.2676	{'accuracy': 0.901}
No log	3.0	60	0.2518	{'accuracy': 0.895}
No log	4.0	80	0.2504	{'accuracy': 0.903}

Framework versions

PEFT 0.12.0
Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 3.0.0
Tokenizers 0.19.1

Library: peft
License: apache-2.0
Created: Sep 18, 2024
Updated: Sep 18, 2024