speecht5_finetune_binisha
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: 0.3836
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 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: 1500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6028 | 2.7586 | 100 | 0.5187 |
| 0.5195 | 5.5172 | 200 | 0.4851 |
| 0.5075 | 8.2759 | 300 | 0.4708 |
| 0.462 | 11.0345 | 400 | 0.4609 |
| 0.4429 | 13.7931 | 500 | 0.4294 |
| 0.4303 | 16.5517 | 600 | 0.4249 |
| 0.4172 | 19.3103 | 700 | 0.4184 |
| 0.402 | 22.0690 | 800 | 0.4077 |
| 0.3898 | 24.8276 | 900 | 0.3975 |
| 0.3966 | 27.5862 | 1000 | 0.4197 |
| 0.3773 | 30.3448 | 1100 | 0.3955 |
| 0.3658 | 33.1034 | 1200 | 0.3878 |
| 0.3644 | 35.8621 | 1300 | 0.3878 |
| 0.3622 | 38.6207 | 1400 | 0.3841 |
| 0.3671 | 41.3793 | 1500 | 0.3836 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for binisha/speecht5_finetune_binisha
Base model
microsoft/speecht5_tts