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hung200504/
bert-covidqa-5

Name: bert-covidqa-5
Rating: 2.5 (8 reviews)

generated_from_trainer

covid_qa_deepset

timpal0l/mdeberta-v3-base-squad2

finetune

mit

endpoints_compatible

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bert-covidqa-5

This model is a fine-tuned version of timpal0l/mdeberta-v3-base-squad2 on the covid_qa_deepset dataset. It achieves the following results on the evaluation set:

Loss: 0.4190

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: 3e-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: 1

Training results

Training Loss	Epoch	Step	Validation Loss
0.5956	0.04	5	0.4016
0.3741	0.09	10	0.3879
0.3405	0.13	15	0.4240
0.4372	0.18	20	0.4102
0.2592	0.22	25	0.4534
0.3534	0.26	30	0.4571
0.4268	0.31	35	0.4107
0.2663	0.35	40	0.4166
0.143	0.39	45	0.4345
0.2494	0.44	50	0.5575
0.8953	0.48	55	0.6172
0.5504	0.53	60	0.4879
0.6411	0.57	65	0.3718
0.5454	0.61	70	0.3929
0.4441	0.66	75	0.3641
0.2922	0.7	80	0.3638
0.491	0.75	85	0.3785
0.4362	0.79	90	0.3938
0.1633	0.83	95	0.4162
0.6762	0.88	100	0.4321
0.3111	0.92	105	0.4241
0.3453	0.96	110	0.4190

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.5
Tokenizers 0.14.1

hung200504/bert-covidqa-5

bert-covidqa-5

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hung200504/
bert-covidqa-5