prompt_fine_tuned_boolq_bert

tjasad/prompt_fine_tuned_boolq_bert

prompt_fine_tuned_boolq_bert is a machine learning model from tjasad. 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
Model type: bert
Access: Public
Created: May 3, 2024
Updated: May 3, 2024
SHA: 063850a9

Base models

google-bert/bert-base-uncased

Model card

From the Hugging Face model README

prompt_fine_tuned_boolq_bert

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: 0.6444
Accuracy: 0.8333
F1: 0.7914

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
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	12	0.6844	0.5	0.5333
No log	2.0	24	0.6700	0.6111	0.6408
No log	3.0	36	0.6572	0.7778	0.7778
No log	4.0	48	0.6492	0.8333	0.7914
No log	5.0	60	0.6454	0.8333	0.7914
No log	6.0	72	0.6444	0.8333	0.7914

Framework versions

PEFT 0.10.0
Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1

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