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speecht5_finetuned_yoruba_500_v2 – AI Model by Emmanuelprime | AlphaNeural AI
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Emmanuelprime
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speecht5_finetuned_yoruba_500_v2
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transformers
tensorboard
safetensors
speecht5
text-to-audio
generated_from_trainer
microsoft/speecht5_tts
finetune
mit
endpoints_compatible
us
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speecht5_finetuned_yoruba_500_v2
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: 0.4526
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: 0.0001
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
lr_scheduler_warmup_steps: 100
training_steps: 500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.612
4.4444
100
0.5229
0.5444
8.8889
200
0.4872
0.5166
13.3333
300
0.4702
0.5004
17.7778
400
0.4624
0.4891
22.2222
500
0.4526
Framework versions
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1
