---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: dgo-tts-training-data-a-speecht5
  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. -->

# dgo-tts-training-data-a-speecht5

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4943

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 4000
- training_steps: 40000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step  | Validation Loss |
|:-------------:|:--------:|:-----:|:---------------:|
| 0.6491        | 5.3763   | 1000  | 0.6131          |
| 0.5683        | 10.7527  | 2000  | 0.5488          |
| 0.543         | 16.1290  | 3000  | 0.5120          |
| 0.5203        | 21.5054  | 4000  | 0.5201          |
| 0.5149        | 26.8817  | 5000  | 0.5136          |
| 0.4962        | 32.2581  | 6000  | 0.4971          |
| 0.488         | 37.6344  | 7000  | 0.4969          |
| 0.4742        | 43.0108  | 8000  | 0.4880          |
| 0.4746        | 48.3871  | 9000  | 0.4941          |
| 0.4634        | 53.7634  | 10000 | 0.4886          |
| 0.4491        | 59.1398  | 11000 | 0.4912          |
| 0.4416        | 64.5161  | 12000 | 0.4854          |
| 0.4388        | 69.8925  | 13000 | 0.4894          |
| 0.4263        | 75.2688  | 14000 | 0.4911          |
| 0.425         | 80.6452  | 15000 | 0.4853          |
| 0.4179        | 86.0215  | 16000 | 0.4862          |
| 0.4205        | 91.3978  | 17000 | 0.4882          |
| 0.4087        | 96.7742  | 18000 | 0.4869          |
| 0.4079        | 102.1505 | 19000 | 0.4898          |
| 0.4142        | 107.5269 | 20000 | 0.4892          |
| 0.4132        | 112.9032 | 21000 | 0.4937          |
| 0.4126        | 118.2796 | 22000 | 0.4908          |
| 0.4091        | 123.6559 | 23000 | 0.4901          |
| 0.4078        | 129.0323 | 24000 | 0.4886          |
| 0.4167        | 134.4086 | 25000 | 0.4926          |
| 0.4052        | 139.7849 | 26000 | 0.4906          |
| 0.4057        | 145.1613 | 27000 | 0.4905          |
| 0.408         | 150.5376 | 28000 | 0.4919          |
| 0.4054        | 155.9140 | 29000 | 0.4896          |
| 0.4096        | 161.2903 | 30000 | 0.4920          |
| 0.4087        | 166.6667 | 31000 | 0.4922          |
| 0.3987        | 172.0430 | 32000 | 0.4911          |
| 0.4006        | 177.4194 | 33000 | 0.4934          |
| 0.4017        | 182.7957 | 34000 | 0.4936          |
| 0.4           | 188.1720 | 35000 | 0.4923          |
| 0.401         | 193.5484 | 36000 | 0.4941          |
| 0.3984        | 198.9247 | 37000 | 0.4946          |
| 0.401         | 204.3011 | 38000 | 0.4923          |
| 0.4012        | 209.6774 | 39000 | 0.4945          |
| 0.396         | 215.0538 | 40000 | 0.4943          |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.22.1