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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: 0.5093
## 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: 4
- 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: 15000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| No log | 11.36 | 250 | 0.5773 |
| 0.6817 | 22.73 | 500 | 0.4226 |
| 0.6817 | 34.09 | 750 | 0.4172 |
| 0.4227 | 45.45 | 1000 | 0.4403 |
| 0.4227 | 56.82 | 1250 | 0.4363 |
| 0.3798 | 68.18 | 1500 | 0.4678 |
| 0.3798 | 79.55 | 1750 | 0.4609 |
| 0.3629 | 90.91 | 2000 | 0.4706 |
| 0.3629 | 102.27 | 2250 | 0.4558 |
| 0.3534 | 113.64 | 2500 | 0.4697 |
| 0.3534 | 125.0 | 2750 | 0.4641 |
| 0.3429 | 136.36 | 3000 | 0.4813 |
| 0.3429 | 147.73 | 3250 | 0.4933 |
| 0.3354 | 159.09 | 3500 | 0.5028 |
| 0.3354 | 170.45 | 3750 | 0.4860 |
| 0.3247 | 181.82 | 4000 | 0.4945 |
| 0.3247 | 193.18 | 4250 | 0.5021 |
| 0.3227 | 204.55 | 4500 | 0.4802 |
| 0.3227 | 215.91 | 4750 | 0.4874 |
| 0.3173 | 227.27 | 5000 | 0.4917 |
| 0.3173 | 238.64 | 5250 | 0.4913 |
| 0.3124 | 250.0 | 5500 | 0.5010 |
| 0.3124 | 261.36 | 5750 | 0.4846 |
| 0.3044 | 272.73 | 6000 | 0.5064 |
| 0.3044 | 284.09 | 6250 | 0.5071 |
| 0.304 | 295.45 | 6500 | 0.5009 |
| 0.304 | 306.82 | 6750 | 0.4901 |
| 0.2991 | 318.18 | 7000 | 0.4887 |
| 0.2991 | 329.55 | 7250 | 0.4908 |
| 0.2981 | 340.91 | 7500 | 0.4866 |
| 0.2981 | 352.27 | 7750 | 0.4972 |
| 0.296 | 363.64 | 8000 | 0.5037 |
| 0.296 | 375.0 | 8250 | 0.5099 |
| 0.2956 | 386.36 | 8500 | 0.4939 |
| 0.2956 | 397.73 | 8750 | 0.5055 |
| 0.2895 | 409.09 | 9000 | 0.5012 |
| 0.2895 | 420.45 | 9250 | 0.5231 |
| 0.2918 | 431.82 | 9500 | 0.5082 |
| 0.2918 | 443.18 | 9750 | 0.5120 |
| 0.289 | 454.55 | 10000 | 0.5067 |
| 0.289 | 465.91 | 10250 | 0.5097 |
| 0.287 | 477.27 | 10500 | 0.5244 |
| 0.287 | 488.64 | 10750 | 0.5116 |
| 0.2836 | 500.0 | 11000 | 0.5073 |
| 0.2836 | 511.36 | 11250 | 0.5089 |
| 0.2864 | 522.73 | 11500 | 0.5145 |
| 0.2864 | 534.09 | 11750 | 0.5077 |
| 0.2831 | 545.45 | 12000 | 0.5006 |
| 0.2831 | 556.82 | 12250 | 0.5145 |
| 0.2824 | 568.18 | 12500 | 0.5124 |
| 0.2824 | 579.55 | 12750 | 0.5166 |
| 0.2836 | 590.91 | 13000 | 0.5174 |
| 0.2836 | 602.27 | 13250 | 0.5082 |
| 0.2814 | 613.64 | 13500 | 0.5157 |
| 0.2814 | 625.0 | 13750 | 0.5210 |
| 0.2813 | 636.36 | 14000 | 0.5161 |
| 0.2813 | 647.73 | 14250 | 0.5092 |
| 0.2804 | 659.09 | 14500 | 0.5131 |
| 0.2804 | 670.45 | 14750 | 0.5128 |
| 0.2796 | 681.82 | 15000 | 0.5093 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.14.1
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