bert-base-uncased-finetuned-infovqa

tiennvcs/bert-base-uncased-finetuned-infovqa

bert-base-uncased-finetuned-infovqa is a question answering model from tiennvcs. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

1% of all-time downloads

All-time downloads

432

Public

Repo size

871 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin436 MB · 100%

At a glance

Task: Question Answering
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Mar 2, 2022
Updated: Oct 23, 2021
SHA: cf6ab4e7

Try a prompt

Model card

From the Hugging Face model README

bert-base-uncased-finetuned-infovqa

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

Loss: 2.8276

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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 250500
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
3.2765	0.23	1000	3.0678
2.9987	0.46	2000	2.9525
2.826	0.69	3000	2.7870
2.7084	0.93	4000	2.7051
2.1286	1.16	5000	2.9286
2.0009	1.39	6000	3.1037
2.0323	1.62	7000	2.8567
1.9905	1.85	8000	2.8276

Framework versions

Transformers 4.10.0
Pytorch 1.8.0+cu101
Datasets 1.11.0
Tokenizers 0.10.3

Task: Question Answering
Library: transformers
Type: bert
License: apache-2.0
Created: Mar 2, 2022
Updated: Oct 23, 2021