QA_SYNTH_DATA_WITH_UNANSWERABLE_28_AUG_v1

am-infoweb/QA_SYNTH_DATA_WITH_UNANSWERABLE_28_AUG_v1

QA_SYNTH_DATA_WITH_UNANSWERABLE_28_AUG_v1 is a question answering model from am-infoweb. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as mit.

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

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At a glance

Task: Question Answering
Library: transformers
License: mit
Model type: xlm-roberta
Access: Public
Created: Aug 28, 2023
Updated: Aug 28, 2023
SHA: 65fee55e

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Base models

Model card

From the Hugging Face model README

QA_SYNTH_DATA_WITH_UNANSWERABLE_28_AUG_v1

This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0031

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: 2
eval_batch_size: 2
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
0.1645	1.0	13141	0.1139
0.0279	2.0	26282	0.0459
0.1305	3.0	39423	0.0819
0.0009	4.0	52564	0.0076
0.0234	5.0	65705	0.0082
0.0	6.0	78846	0.0123
0.0063	7.0	91987	0.0050
0.0137	8.0	105128	0.0044
0.0	9.0	118269	0.0031
0.0	10.0	131410	0.0031

Framework versions

Transformers 4.32.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.14.4
Tokenizers 0.13.3

Task: Question Answering
Library: transformers
Type: xlm-roberta
License: mit
Created: Aug 28, 2023
Updated: Aug 28, 2023