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speecht5_tts_swahili – AI Model by Hidi-agili | AlphaNeural AI
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Hidi-agili
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speecht5_tts_swahili
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transformers
tensorboard
safetensors
speecht5
text-to-audio
generated_from_trainer
sw
mozilla-foundation/common_voice_17_0
microsoft/speecht5_tts
finetune
mit
endpoints_compatible
us
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Swahili TTS
This model is a fine-tuned version of
microsoft/speecht5_tts
on the Swahili dataset. It achieves the following results on the evaluation set:
Loss: 0.5318
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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
0.6394
1.3351
1000
0.5669
0.591
2.6702
2000
0.5440
0.5796
4.0053
3000
0.5352
0.5689
5.3405
4000
0.5318
Framework versions
Transformers 4.50.0.dev0
Pytorch 2.5.1+cu124
Datasets 3.3.2
Tokenizers 0.21.0
