distilbert-base-uncased-lora-text-classification

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

distilbert-base-uncased-lora-text-classification is a machine learning model from ManuGenard. 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: 6d83b1ad

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: 0.9456
Accuracy: {'accuracy': 0.889}

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	0.6952	{'accuracy': 0.808}
0.4327	2.0	500	0.5493	{'accuracy': 0.857}
0.4327	3.0	750	0.5937	{'accuracy': 0.874}
0.212	4.0	1000	0.6253	{'accuracy': 0.891}
0.212	5.0	1250	0.7137	{'accuracy': 0.884}
0.0841	6.0	1500	0.7189	{'accuracy': 0.89}
0.0841	7.0	1750	0.8318	{'accuracy': 0.892}
0.0273	8.0	2000	0.9064	{'accuracy': 0.892}
0.0273	9.0	2250	0.9400	{'accuracy': 0.89}
0.0068	10.0	2500	0.9456	{'accuracy': 0.889}

Framework versions

PEFT 0.11.1
Transformers 4.41.2
Pytorch 2.3.0
Datasets 2.19.2
Tokenizers 0.19.1

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