Vi-gec5

Huyen2310/Vi-gec5

Vi-gec5 is a machine learning model from Huyen2310. 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: t5
Access: Public
Created: Mar 3, 2023
Updated: Mar 3, 2023
SHA: a04861e9

Model card

From the Hugging Face model README

Vi-gec5

This model is a fine-tuned version of VietAI/vit5-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0927
Wer: 2.9213

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: 5e-06
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 1167
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.7673	0.41	233	0.6208	191.2360
0.4518	0.81	466	0.1819	34.3105
0.2424	1.22	699	0.1073	4.2510
0.2037	1.63	932	0.0955	3.2135
0.1995	2.04	1165	0.0927	2.9213

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2

Library: transformers
Type: t5
License: mit
Created: Mar 3, 2023
Updated: Mar 3, 2023