| | --- |
| | license: mit |
| | base_model: microsoft/speecht5_tts |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: speecht5_jenny_2000sample |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # speecht5_jenny_2000sample |
| |
|
| | This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3933 |
| |
|
| | ## 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: 3e-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 16 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 100 |
| | - training_steps: 1000 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 0.5538 | 0.4444 | 50 | 0.4639 | |
| | | 0.507 | 0.8889 | 100 | 0.4439 | |
| | | 0.4823 | 1.3333 | 150 | 0.4217 | |
| | | 0.4739 | 1.7778 | 200 | 0.4156 | |
| | | 0.4661 | 2.2222 | 250 | 0.4094 | |
| | | 0.4582 | 2.6667 | 300 | 0.4071 | |
| | | 0.439 | 3.1111 | 350 | 0.4024 | |
| | | 0.4499 | 3.5556 | 400 | 0.4038 | |
| | | 0.4379 | 4.0 | 450 | 0.4004 | |
| | | 0.4294 | 4.4444 | 500 | 0.3995 | |
| | | 0.427 | 4.8889 | 550 | 0.3963 | |
| | | 0.4262 | 5.3333 | 600 | 0.3957 | |
| | | 0.4319 | 5.7778 | 650 | 0.3959 | |
| | | 0.4171 | 6.2222 | 700 | 0.3948 | |
| | | 0.4248 | 6.6667 | 750 | 0.3967 | |
| | | 0.4195 | 7.1111 | 800 | 0.3946 | |
| | | 0.4174 | 7.5556 | 850 | 0.3939 | |
| | | 0.4183 | 8.0 | 900 | 0.3945 | |
| | | 0.4107 | 8.4444 | 950 | 0.3934 | |
| | | 0.422 | 8.8889 | 1000 | 0.3933 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.41.2 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| |
|
