distilbert-base-uncased-lora-text-classification

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

distilbert-base-uncased-lora-text-classification is a machine learning model from AurrieMartinez. 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: Jun 5, 2024
Updated: Jun 5, 2024
SHA: e4ff617d

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: 0.9743
Accuracy: {'accuracy': 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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	250	0.5011	{'accuracy': 0.849}
0.4507	2.0	500	0.3976	{'accuracy': 0.887}
0.4507	3.0	750	0.5992	{'accuracy': 0.891}
0.1928	4.0	1000	0.6172	{'accuracy': 0.897}
0.1928	5.0	1250	0.7082	{'accuracy': 0.89}
0.0827	6.0	1500	0.8177	{'accuracy': 0.89}
0.0827	7.0	1750	0.8743	{'accuracy': 0.886}
0.0127	8.0	2000	0.9673	{'accuracy': 0.892}
0.0127	9.0	2250	0.9793	{'accuracy': 0.89}
0.0103	10.0	2500	0.9743	{'accuracy': 0.89}

Framework versions

PEFT 0.11.1
Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1

Library: peft
License: apache-2.0
Created: Jun 5, 2024
Updated: Jun 5, 2024