transformers tensorboard safetensors speecht5 text-to-audio generated_from_trainer dataset:common_voice_13_0 base_model:microsoft/speecht5_tts license:mit endpoints_compatible region:us
---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
model-index:
- name: speecht5_tts_commonvoice_fa
  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_commonvoice_fa

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4695

## 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: 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6592        | 1.59  | 250  | 0.5820          |
| 0.642         | 3.18  | 500  | 0.5502          |
| 0.5755        | 4.78  | 750  | 0.5452          |
| 0.5743        | 6.37  | 1000 | 0.5236          |
| 0.5542        | 7.96  | 1250 | 0.5206          |
| 0.5543        | 9.55  | 1500 | 0.5192          |
| 0.5266        | 11.15 | 1750 | 0.5011          |
| 0.5234        | 12.74 | 2000 | 0.4945          |
| 0.5139        | 14.33 | 2250 | 0.4873          |
| 0.5143        | 15.92 | 2500 | 0.4797          |
| 0.5051        | 17.52 | 2750 | 0.4811          |
| 0.4873        | 19.11 | 3000 | 0.4724          |
| 0.4922        | 20.7  | 3250 | 0.4681          |
| 0.4864        | 22.29 | 3500 | 0.4695          |
| 0.4769        | 23.89 | 3750 | 0.4702          |
| 0.4691        | 25.48 | 4000 | 0.4695          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
