speecht5_finetuned_voxpopuli

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

• validation Loss: 0.5676
• training loss: 0.38

Model description

text-to-speech

Intended uses & limitations

text to speech, stst models

Training and evaluation data

finetuning using the voxpopuli dataset for the Lithuanian language, in this case there were few speakers and few examples, so the training gives us 0.56 validation loss and 0.38 of training loss, This means the model may not generalize well to new data it hasn't seen before. To avoid overfitting, you can try some regularization techniques, such as dropout, batch normalization, or model size reduction.

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• 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: 500
• training_steps: 4000

Training results

Training Loss	Epoch	Step	Validation Loss
0.443	380.95	1000	0.5600
0.4045	761.9	2000	0.5717
0.3877	1142.86	3000	0.5647
0.3845	1523.81	4000	0.5676

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.0
• Datasets 2.1.0
• Tokenizers 0.13.3