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---
language:
- en
license: mit
base_model: microsoft/speecht5_tts
tags:
- en_accent,mozilla,t5,common_voice_1_0
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_1_0
model-index:
- name: SpeechT5 TTS English Accented
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 English Accented
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the Common Voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5154
## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| No log | 2.72 | 250 | 0.6947 |
| 0.7897 | 5.43 | 500 | 0.5278 |
| 0.7897 | 8.15 | 750 | 0.5005 |
| 0.5429 | 10.87 | 1000 | 0.4842 |
| 0.5429 | 13.59 | 1250 | 0.4830 |
| 0.4997 | 16.3 | 1500 | 0.4912 |
| 0.4997 | 19.02 | 1750 | 0.4820 |
| 0.4712 | 21.74 | 2000 | 0.4835 |
| 0.4712 | 24.46 | 2250 | 0.4840 |
| 0.4621 | 27.17 | 2500 | 0.4925 |
| 0.4621 | 29.89 | 2750 | 0.4855 |
| 0.4507 | 32.61 | 3000 | 0.4882 |
| 0.4507 | 35.33 | 3250 | 0.5065 |
| 0.4445 | 38.04 | 3500 | 0.5033 |
| 0.4445 | 40.76 | 3750 | 0.4991 |
| 0.4345 | 43.48 | 4000 | 0.4950 |
| 0.4345 | 46.2 | 4250 | 0.4986 |
| 0.4306 | 48.91 | 4500 | 0.5026 |
| 0.4306 | 51.63 | 4750 | 0.4986 |
| 0.4272 | 54.35 | 5000 | 0.5048 |
| 0.4272 | 57.07 | 5250 | 0.4967 |
| 0.4234 | 59.78 | 5500 | 0.5011 |
| 0.4234 | 62.5 | 5750 | 0.5017 |
| 0.4187 | 65.22 | 6000 | 0.5047 |
| 0.4187 | 67.93 | 6250 | 0.5041 |
| 0.4188 | 70.65 | 6500 | 0.5064 |
| 0.4188 | 73.37 | 6750 | 0.5164 |
| 0.4108 | 76.09 | 7000 | 0.5133 |
| 0.4108 | 78.8 | 7250 | 0.5086 |
| 0.4118 | 81.52 | 7500 | 0.5070 |
| 0.4118 | 84.24 | 7750 | 0.5093 |
| 0.4082 | 86.96 | 8000 | 0.5155 |
| 0.4082 | 89.67 | 8250 | 0.5089 |
| 0.407 | 92.39 | 8500 | 0.5134 |
| 0.407 | 95.11 | 8750 | 0.5056 |
| 0.407 | 97.83 | 9000 | 0.5154 |
| 0.407 | 100.54 | 9250 | 0.5108 |
| 0.4062 | 103.26 | 9500 | 0.5112 |
| 0.4062 | 105.98 | 9750 | 0.5122 |
| 0.4052 | 108.7 | 10000 | 0.5154 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.14.1
|