20230430-001-baseline-mbert-qa-ft-clickbait-spoiling

intanm/20230430-001-baseline-mbert-qa-ft-clickbait-spoiling

20230430-001-baseline-mbert-qa-ft-clickbait-spoiling is a question answering model from intanm. 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. --

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At a glance

Task: Question Answering
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Apr 30, 2023
Updated: Apr 30, 2023
SHA: ccb4a3b4

Try a prompt

Model card

From the Hugging Face model README

20230430-001-baseline-mbert-qa-ft-clickbait-spoiling

This model is a fine-tuned version of intanm/mBERT-squad on the None dataset. It achieves the following results on the evaluation set:

Loss: 4.9090

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	200	2.8250
No log	2.0	400	2.7890
2.5758	3.0	600	3.0925
2.5758	4.0	800	3.5365
1.1707	5.0	1000	3.9249
1.1707	6.0	1200	4.2093
1.1707	7.0	1400	4.4076
0.4982	8.0	1600	4.7308
0.4982	9.0	1800	4.8659
0.2732	10.0	2000	4.9090

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3

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