ceb_full_checkpoint

mikhail-panzo/ceb_full_checkpoint

ceb_full_checkpoint is a text-to-audio model from mikhail-panzo. 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. --

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At a glance

Task: Text-to-Audio
Library: transformers
License: mit
Model type: speecht5
Access: Public
Created: Apr 14, 2024
Updated: Apr 14, 2024
SHA: 915fad23

Base models

Model card

From the Hugging Face model README

ceb_full_checkpoint

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

Loss: 0.3917

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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.4492	19.23	500	0.4096
0.429	38.46	1000	0.3978
0.4188	57.69	1500	0.3947
0.4142	76.92	2000	0.3921
0.4105	96.15	2500	0.3921
0.4081	115.38	3000	0.3914
0.4107	134.62	3500	0.3906
0.406	153.85	4000	0.3917

Framework versions

Transformers 4.40.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Task: Text-to-Audio
Library: transformers
Type: speecht5
License: mit
Created: Apr 14, 2024
Updated: Apr 14, 2024