kobigbird-bert-base-finetuned-klue-v2_epoch64

Seongmi/kobigbird-bert-base-finetuned-klue-v2_epoch64

kobigbird-bert-base-finetuned-klue-v2_epoch64 is a question answering model from Seongmi. Use it when the input is a question plus a passage. It is set up for transformers.

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

Downloads · 30 days

3% of all-time downloads

All-time downloads

577

Public

Repo size

2.8 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin472 MB · 100%

At a glance

Task: Question Answering
Library: transformers
Model type: big_bird
Access: Public
Created: Oct 10, 2022
Updated: Oct 11, 2022
SHA: 7331eecf

Try a prompt

Model card

From the Hugging Face model README

kobigbird-bert-base-finetuned-klue-v2_epoch64

This model is a fine-tuned version of monologg/kobigbird-bert-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.8139

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: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss
1.5026	0.55	500	1.3754
0.9551	1.1	1000	0.9633
0.8	1.64	1500	0.8191
0.6182	2.19	2000	0.7808
0.5731	2.74	2500	0.7482
0.3699	3.29	3000	0.8175
0.3634	3.84	3500	0.8139

Framework versions

Transformers 4.23.0
Pytorch 1.12.1+cu113
Datasets 2.5.2
Tokenizers 0.13.1

Task: Question Answering
Library: transformers
Type: big_bird
Created: Oct 10, 2022
Updated: Oct 11, 2022