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speecht5_pt_full
This model is a fine-tuned version of microsoft/speecht5_tts on the mozilla-foundation/common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5021
DISCLAIMER: This model is trained for the sole purpose of finishing the HuggingFace Audio course. It doesn't have any usability and outputs pure noise. If you have an idea of how to improve the model, feel free to create a post in the Community tab of this model. Thank you!
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: 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: 300
- training_steps: 2000
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.8882 | 0.18 | 100 | 0.7494 |
0.7726 | 0.36 | 200 | 0.6657 |
0.642 | 0.54 | 300 | 0.5767 |
0.6042 | 0.71 | 400 | 0.5545 |
0.5972 | 0.89 | 500 | 0.5342 |
0.5832 | 1.07 | 600 | 0.5337 |
0.5851 | 1.25 | 700 | 0.5291 |
0.5744 | 1.43 | 800 | 0.5245 |
0.5638 | 1.61 | 900 | 0.5186 |
0.5562 | 1.78 | 1000 | 0.5174 |
0.56 | 1.96 | 1100 | 0.5133 |
0.5446 | 2.14 | 1200 | 0.5113 |
0.5556 | 2.32 | 1300 | 0.5099 |
0.5457 | 2.5 | 1400 | 0.5071 |
0.5504 | 2.68 | 1500 | 0.5087 |
0.5497 | 2.85 | 1600 | 0.5039 |
0.545 | 3.03 | 1700 | 0.5034 |
0.5503 | 3.21 | 1800 | 0.5051 |
0.5621 | 3.39 | 1900 | 0.5040 |
0.5347 | 3.57 | 2000 | 0.5021 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1