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---
language:
- as
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- google/fluers
model-index:
- name: SpeechT5 TTS Assamese
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 TTS Assamese
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the Google fluers dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3991
## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 200
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 0.4812 | 30.7692 | 200 | 0.4176 |
| 0.4038 | 61.5385 | 400 | 0.4009 |
| 0.3862 | 92.3077 | 600 | 0.3885 |
| 0.3433 | 123.0769 | 800 | 0.3843 |
| 0.3252 | 153.8462 | 1000 | 0.3991 |
### Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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