bert_qa_model_electronics_1

Chetna19/bert_qa_model_electronics_1

bert_qa_model_electronics_1 is a question answering model from Chetna19. 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

2% of all-time downloads

All-time downloads

333

Public

Repo size

2.7 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin1.3 GB · 100%

At a glance

Task: Question Answering
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: May 30, 2023
Updated: May 30, 2023
SHA: ef0af03f

Try a prompt

Datasets

subjqa

Model card

From the Hugging Face model README

bert_qa_model_electronics_1

This model is a fine-tuned version of bert-large-uncased-whole-word-masking-finetuned-squad on the subjqa dataset. It achieves the following results on the evaluation set:

Loss: 11.8500

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	32	11.5214
No log	2.0	64	11.1691
No log	3.0	96	11.6369
No log	4.0	128	11.7854
No log	5.0	160	11.8500

Framework versions

Transformers 4.28.0
Pytorch 1.13.0a0+d321be6
Datasets 2.12.0
Tokenizers 0.13.3

Task: Question Answering
Library: transformers
Type: bert
License: apache-2.0
Created: May 30, 2023
Updated: May 30, 2023