lora_fine_tuned_boolq

lenatr99/lora_fine_tuned_boolq

lora_fine_tuned_boolq is a machine learning model from lenatr99. 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: May 3, 2024
Updated: May 3, 2024
SHA: 920ab543

Base models

google-bert/bert-base-uncased

Model card

From the Hugging Face model README

lora_fine_tuned_boolq

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

Loss: 0.5547
Accuracy: 0.7778
F1: 0.6806

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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 400

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6762	4.1667	50	0.5947	0.7778	0.6806
0.6639	8.3333	100	0.5719	0.7778	0.6806
0.6555	12.5	150	0.5648	0.7778	0.6806
0.6605	16.6667	200	0.5615	0.7778	0.6806
0.6612	20.8333	250	0.5568	0.7778	0.6806
0.6508	25.0	300	0.5567	0.7778	0.6806
0.6491	29.1667	350	0.5550	0.7778	0.6806
0.663	33.3333	400	0.5547	0.7778	0.6806

Framework versions

PEFT 0.10.1.dev0
Transformers 4.40.1
Pytorch 2.3.0
Datasets 2.19.0
Tokenizers 0.19.1

Library: peft
License: apache-2.0
Created: May 3, 2024
Updated: May 3, 2024