metadata
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_Mar
results: []
speecht5_finetuned_Mar
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: 0.4785
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use 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: 50
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.6818 | 0.7976 | 100 | 0.6565 |
0.6107 | 1.5952 | 200 | 0.5797 |
0.6033 | 2.3928 | 300 | 0.5716 |
0.5893 | 3.1904 | 400 | 0.5686 |
0.5919 | 3.9880 | 500 | 0.5624 |
0.5732 | 4.7856 | 600 | 0.5932 |
0.5677 | 5.5833 | 700 | 0.5485 |
0.5521 | 6.3809 | 800 | 0.5407 |
0.5513 | 7.1785 | 900 | 0.5348 |
0.5488 | 7.9761 | 1000 | 0.5366 |
0.5344 | 8.7737 | 1100 | 0.5267 |
0.5329 | 9.5713 | 1200 | 0.5163 |
0.5118 | 10.3689 | 1300 | 0.5172 |
0.5126 | 11.1665 | 1400 | 0.5089 |
0.5256 | 11.9641 | 1500 | 0.5104 |
0.5126 | 12.7617 | 1600 | 0.5054 |
0.5034 | 13.5593 | 1700 | 0.5023 |
0.4986 | 14.3569 | 1800 | 0.4974 |
0.4926 | 15.1545 | 1900 | 0.5081 |
0.4961 | 15.9521 | 2000 | 0.4929 |
0.4886 | 16.7498 | 2100 | 0.4863 |
0.491 | 17.5474 | 2200 | 0.4925 |
0.4845 | 18.3450 | 2300 | 0.4859 |
0.4726 | 19.1426 | 2400 | 0.4835 |
0.4786 | 19.9402 | 2500 | 0.4829 |
0.4732 | 20.7378 | 2600 | 0.4800 |
0.4713 | 21.5354 | 2700 | 0.4737 |
0.4571 | 22.3330 | 2800 | 0.4789 |
0.4559 | 23.1306 | 2900 | 0.4771 |
0.4552 | 23.9282 | 3000 | 0.4785 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3