---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: fil_b64_le4_s8000
  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. -->

# fil_b64_le4_s8000

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4246

## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 0.4811        | 22.2222  | 500  | 0.4381          |
| 0.4495        | 44.4444  | 1000 | 0.4216          |
| 0.4293        | 66.6667  | 1500 | 0.4446          |
| 0.4246        | 88.8889  | 2000 | 0.4177          |
| 0.4094        | 111.1111 | 2500 | 0.4179          |
| 0.3944        | 133.3333 | 3000 | 0.4232          |
| 0.3794        | 155.5556 | 3500 | 0.4190          |
| 0.3768        | 177.7778 | 4000 | 0.4187          |
| 0.3743        | 200.0    | 4500 | 0.4276          |
| 0.3598        | 222.2222 | 5000 | 0.4232          |
| 0.3634        | 244.4444 | 5500 | 0.4203          |
| 0.3558        | 266.6667 | 6000 | 0.4219          |
| 0.3502        | 288.8889 | 6500 | 0.4230          |
| 0.3529        | 311.1111 | 7000 | 0.4268          |
| 0.3447        | 333.3333 | 7500 | 0.4254          |
| 0.3371        | 355.5556 | 8000 | 0.4246          |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1