QA_REDACTION_NOV1_19

prajwalJumde/QA_REDACTION_NOV1_19

QA_REDACTION_NOV1_19 is a question answering model from prajwalJumde. 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. --

Downloads · 30 days

17% of all-time downloads

All-time downloads

Public

Repo size

2.2 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin1.1 GB · 98%

At a glance

Task: Question Answering
Library: transformers
License: mit
Model type: xlm-roberta
Access: Public
Created: Nov 1, 2023
Updated: Nov 1, 2023
SHA: f258e5f2

Try a prompt

Base models

Model card

From the Hugging Face model README

QA_REDACTION_NOV1_19

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: 0.0174

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: 3
eval_batch_size: 3
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
1.0179	1.0	945	0.0366
0.1597	2.0	1890	0.0217
0.0651	3.0	2835	0.0264
0.0815	4.0	3780	0.0241
0.0503	5.0	4725	0.0213
0.0215	6.0	5670	0.0160
0.0257	7.0	6615	0.0195
0.0268	8.0	7560	0.0194
0.0323	9.0	8505	0.0179
0.0215	10.0	9450	0.0174

Framework versions

Transformers 4.34.1
Pytorch 2.0.1
Datasets 2.14.6
Tokenizers 0.14.1

Task: Question Answering
Library: transformers
Type: xlm-roberta
License: mit
Created: Nov 1, 2023
Updated: Nov 1, 2023