speecht5_finetuned_metalsongs

nichonifroa/speecht5_finetuned_metalsongs

speecht5_finetuned_metalsongs is a text-to-audio model from nichonifroa. Use it for the text-to-audio 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. --

Downloads · 30 days

2% of all-time downloads

All-time downloads

279

Public

Repo size

3.5 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin578 MB · 100%

At a glance

Task: Text-to-Audio
Library: transformers
License: mit
Model type: speecht5
Access: Public
Created: Jul 24, 2023
Updated: Jul 24, 2023
SHA: 3602ae58

Base models

microsoft/speecht5_tts

Model card

From the Hugging Face model README

speecht5_finetuned_metalsongs

This model is a fine-tuned version of microsoft/speecht5_tts on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4426

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: 1e-05
train_batch_size: 4
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss
0.5213	34.78	100	0.5506
0.436	69.57	200	0.4810
0.4004	104.35	300	0.4776
0.3816	139.13	400	0.4639
0.3644	173.91	500	0.4536
0.3583	208.7	600	0.4539
0.3515	243.48	700	0.4476
0.3534	278.26	800	0.4489
0.3471	313.04	900	0.4466
0.3463	347.83	1000	0.4426

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

Task: Text-to-Audio
Library: transformers
Type: speecht5
License: mit
Created: Jul 24, 2023
Updated: Jul 24, 2023