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---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
model-index:
- name: speecht5_finetuned_local_language_dataset_bn
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_finetuned_local_language_dataset_bn
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6038
## 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: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8489 | 0.1675 | 100 | 0.7253 |
| 0.7415 | 0.3349 | 200 | 0.6669 |
| 0.6951 | 0.5024 | 300 | 0.6351 |
| 0.6798 | 0.6699 | 400 | 0.6267 |
| 0.6757 | 0.8373 | 500 | 0.6246 |
| 0.674 | 1.0048 | 600 | 0.6127 |
| 0.6728 | 1.1723 | 700 | 0.6087 |
| 0.6599 | 1.3398 | 800 | 0.6061 |
| 0.6527 | 1.5072 | 900 | 0.6048 |
| 0.6583 | 1.6747 | 1000 | 0.6038 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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