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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: Hindi_SpeechT5_finetuned
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. -->
# Hindi_SpeechT5_finetuned
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: 0.4484
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.6781 | 0.3442 | 100 | 0.5528 |
| 0.5834 | 0.6885 | 200 | 0.5470 |
| 0.554 | 1.0327 | 300 | 0.5090 |
| 0.5397 | 1.3769 | 400 | 0.5025 |
| 0.526 | 1.7212 | 500 | 0.4872 |
| 0.5224 | 2.0654 | 600 | 0.4846 |
| 0.515 | 2.4096 | 700 | 0.4754 |
| 0.5047 | 2.7539 | 800 | 0.4703 |
| 0.5014 | 3.0981 | 900 | 0.4689 |
| 0.4946 | 3.4423 | 1000 | 0.4601 |
| 0.4912 | 3.7866 | 1100 | 0.4584 |
| 0.4847 | 4.1308 | 1200 | 0.4554 |
| 0.4824 | 4.4750 | 1300 | 0.4514 |
| 0.4831 | 4.8193 | 1400 | 0.4501 |
| 0.4723 | 5.1635 | 1500 | 0.4484 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
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