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jelle – Dataset by HusseinBashir | AlphaNeural AI
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jelle
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: 0.4497
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: 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: 100
training_steps: 500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.5223
3.4622
100
0.4843
0.4818
6.9244
200
0.4572
0.4493
10.3556
300
0.4514
0.4378
13.8178
400
0.4512
0.4281
17.2489
500
0.4497
Framework versions
Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.1
