metadata
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: Youtube3kTTSModel
results: []
Youtube3kTTSModel
This model is a fine-tuned version of microsoft/speecht5_tts on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4839
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6301 | 0.2222 | 100 | 0.5639 |
| 0.6013 | 0.4444 | 200 | 0.5471 |
| 0.5666 | 0.6667 | 300 | 0.5315 |
| 0.5632 | 0.8889 | 400 | 0.5254 |
| 0.5547 | 1.1111 | 500 | 0.5184 |
| 0.5583 | 1.3333 | 600 | 0.5211 |
| 0.5527 | 1.5556 | 700 | 0.5150 |
| 0.5508 | 1.7778 | 800 | 0.5123 |
| 0.5432 | 2.0 | 900 | 0.5135 |
| 0.5478 | 2.2222 | 1000 | 0.5077 |
| 0.5419 | 2.4444 | 1100 | 0.5073 |
| 0.5439 | 2.6667 | 1200 | 0.5083 |
| 0.5381 | 2.8889 | 1300 | 0.5108 |
| 0.5355 | 3.1111 | 1400 | 0.5075 |
| 0.5317 | 3.3333 | 1500 | 0.5053 |
| 0.5345 | 3.5556 | 1600 | 0.5022 |
| 0.5329 | 3.7778 | 1700 | 0.5006 |
| 0.53 | 4.0 | 1800 | 0.4965 |
| 0.5261 | 4.2222 | 1900 | 0.4971 |
| 0.5272 | 4.4444 | 2000 | 0.4976 |
| 0.5272 | 4.6667 | 2100 | 0.4943 |
| 0.5282 | 4.8889 | 2200 | 0.4938 |
| 0.5188 | 5.1111 | 2300 | 0.4980 |
| 0.523 | 5.3333 | 2400 | 0.4894 |
| 0.5225 | 5.5556 | 2500 | 0.4915 |
| 0.5178 | 5.7778 | 2600 | 0.4960 |
| 0.5165 | 6.0 | 2700 | 0.4893 |
| 0.5098 | 6.2222 | 2800 | 0.4892 |
| 0.512 | 6.4444 | 2900 | 0.4868 |
| 0.5177 | 6.6667 | 3000 | 0.4868 |
| 0.5128 | 6.8889 | 3100 | 0.4883 |
| 0.5062 | 7.1111 | 3200 | 0.4852 |
| 0.5104 | 7.3333 | 3300 | 0.4898 |
| 0.5126 | 7.5556 | 3400 | 0.4887 |
| 0.5093 | 7.7778 | 3500 | 0.4908 |
| 0.5075 | 8.0 | 3600 | 0.4828 |
| 0.5029 | 8.2222 | 3700 | 0.4842 |
| 0.5079 | 8.4444 | 3800 | 0.4850 |
| 0.5049 | 8.6667 | 3900 | 0.4853 |
| 0.5034 | 8.8889 | 4000 | 0.4849 |
| 0.4984 | 9.1111 | 4100 | 0.4833 |
| 0.5079 | 9.3333 | 4200 | 0.4863 |
| 0.5023 | 9.5556 | 4300 | 0.4830 |
| 0.5023 | 9.7778 | 4400 | 0.4833 |
| 0.5037 | 10.0 | 4500 | 0.4825 |
| 0.5035 | 10.2222 | 4600 | 0.4822 |
| 0.5011 | 10.4444 | 4700 | 0.4826 |
| 0.4969 | 10.6667 | 4800 | 0.4815 |
| 0.4958 | 10.8889 | 4900 | 0.4839 |
| 0.4972 | 11.1111 | 5000 | 0.4839 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1