Jeolla_encoder

yomilimi/Jeolla_encoder

Jeolla_encoder is a machine learning model from yomilimi. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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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Hugging Face

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At a glance

Library: transformers
License: mit
Model type: bart
Access: Public
Created: Jun 10, 2024
Updated: Jun 10, 2024
SHA: 4b3accb8

Base models

gogamza/kobart-base-v2

Model card

From the Hugging Face model README

Jeolla_encoder

This model is a fine-tuned version of gogamza/kobart-base-v2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0132
Bleu: 89.0781
Gen Len: 14.0615

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Gen Len
0.0168	1.0	15477	0.0157	88.8862	14.0583
0.0143	2.0	30954	0.0136	89.0198	14.0637
0.0123	3.0	46431	0.0132	89.0781	14.0615

Framework versions

Transformers 4.42.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.19.2
Tokenizers 0.19.1

Library: transformers
Type: bart
License: mit
Created: Jun 10, 2024
Updated: Jun 10, 2024