---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: fil_b64_le5_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_le5_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: 0.4119

## 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: 64
- eval_batch_size: 8
- seed: 42
- 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 |
|:-------------:|:--------:|:----:|:---------------:|
| 0.6071        | 21.7391  | 500  | 0.5213          |
| 0.5126        | 43.4783  | 1000 | 0.4507          |
| 0.4749        | 65.2174  | 1500 | 0.4311          |
| 0.454         | 86.9565  | 2000 | 0.4231          |
| 0.443         | 108.6957 | 2500 | 0.4173          |
| 0.4376        | 130.4348 | 3000 | 0.4169          |
| 0.4287        | 152.1739 | 3500 | 0.4133          |
| 0.4264        | 173.9130 | 4000 | 0.4150          |
| 0.423         | 195.6522 | 4500 | 0.4134          |
| 0.4223        | 217.3913 | 5000 | 0.4113          |
| 0.4104        | 239.1304 | 5500 | 0.4098          |
| 0.4192        | 260.8696 | 6000 | 0.4106          |
| 0.4089        | 282.6087 | 6500 | 0.4122          |
| 0.4146        | 304.3478 | 7000 | 0.4115          |
| 0.4116        | 326.0870 | 7500 | 0.4111          |
| 0.4097        | 347.8261 | 8000 | 0.4119          |


### Framework versions

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