bert-base-uncased-pretrain-finetuned-coqa-falttened

alistvt/bert-base-uncased-pretrain-finetuned-coqa-falttened

bert-base-uncased-pretrain-finetuned-coqa-falttened is a question answering model from alistvt. 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

0% of all-time downloads

All-time downloads

4.3K

Public

Repo size

1.3 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin436 MB · 100%

At a glance

Task: Question Answering
Library: transformers
Model type: bert
Access: Public
Created: Mar 2, 2022
Updated: Jan 22, 2022
SHA: b2600736

Try a prompt

Model card

From the Hugging Face model README

bert-base-uncased-pretrain-finetuned-coqa-falttened

This model is a fine-tuned version of alistvt/bert-base-uncased-pretrained-mlm-coqa-stories on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.8655

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: 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: 3

Training results

Training Loss	Epoch	Step	Validation Loss
3.2886	0.29	2000	3.0142
3.0801	0.59	4000	2.8347
2.9744	0.88	6000	2.7643
2.494	1.18	8000	2.7605
2.4417	1.47	10000	2.7790
2.4042	1.77	12000	2.7382
2.1285	2.06	14000	2.8588
2.0569	2.36	16000	2.8937
2.0794	2.65	18000	2.8511
2.0679	2.95	20000	2.8655

Framework versions

Transformers 4.15.0
Pytorch 1.10.0+cu111
Datasets 1.17.0
Tokenizers 0.10.3

Task: Question Answering
Library: transformers
Type: bert
Created: Mar 2, 2022
Updated: Jan 22, 2022