fine_tuned – AI Model by Aaquila | AlphaNeural AI

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Aaquila/
fine_tuned

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microsoft/speecht5_tts

endpoints_compatible

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fine_tuned

This model is a fine-tuned version of microsoft/speecht5_tts on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4328

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: 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: 2500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.5769	8.77	250	0.5205
0.4998	17.54	500	0.4383
0.4637	26.32	750	0.4285
0.4488	35.09	1000	0.4298
0.4307	43.86	1250	0.4272
0.4309	52.63	1500	0.4245
0.4272	61.4	1750	0.4282
0.4204	70.18	2000	0.4317
0.4222	78.95	2250	0.4313
0.4354	87.72	2500	0.4328

Framework versions

Transformers 4.38.1
Pytorch 2.1.0+cu121
Datasets 2.17.0
Tokenizers 0.15.2