---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: fil_b32_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_b32_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: 0.4087

## 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: 2000
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 0.498         | 10.9890  | 500  | 0.4393          |
| 0.448         | 21.9780  | 1000 | 0.4195          |
| 0.4411        | 32.9670  | 1500 | 0.4205          |
| 0.4347        | 43.9560  | 2000 | 0.4253          |
| 0.4173        | 54.9451  | 2500 | 0.4151          |
| 0.4012        | 65.9341  | 3000 | 0.4118          |
| 0.4023        | 76.9231  | 3500 | 0.4092          |
| 0.3873        | 87.9121  | 4000 | 0.4116          |
| 0.381         | 98.9011  | 4500 | 0.4089          |
| 0.3804        | 109.8901 | 5000 | 0.4093          |
| 0.3724        | 120.8791 | 5500 | 0.4066          |
| 0.3665        | 131.8681 | 6000 | 0.4092          |
| 0.3635        | 142.8571 | 6500 | 0.4099          |
| 0.3562        | 153.8462 | 7000 | 0.4075          |
| 0.3581        | 164.8352 | 7500 | 0.4097          |
| 0.3461        | 175.8242 | 8000 | 0.4087          |


### Framework versions

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