---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_improved_data_less_steps
  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_improved_data_less_steps

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: 0.6468

## 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: 8
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- 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: 250
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.4475        | 0.1533 | 25   | 1.1070          |
| 1.3754        | 0.3065 | 50   | 1.0239          |
| 1.2957        | 0.4598 | 75   | 0.9667          |
| 1.1821        | 0.6130 | 100  | 0.9231          |
| 1.1414        | 0.7663 | 125  | 0.8946          |
| 1.0555        | 0.9195 | 150  | 0.8335          |
| 0.9565        | 1.0728 | 175  | 0.7764          |
| 0.9189        | 1.2261 | 200  | 0.7485          |
| 0.8751        | 1.3793 | 225  | 0.7332          |
| 0.8533        | 1.5326 | 250  | 0.7197          |
| 0.8219        | 1.6858 | 275  | 0.7133          |
| 0.8171        | 1.8391 | 300  | 0.7009          |
| 0.8088        | 1.9923 | 325  | 0.6926          |
| 0.785         | 2.1456 | 350  | 0.6877          |
| 0.7989        | 2.2989 | 375  | 0.6824          |
| 0.7755        | 2.4521 | 400  | 0.6784          |
| 0.7914        | 2.6054 | 425  | 0.6738          |
| 0.7696        | 2.7586 | 450  | 0.6694          |
| 0.7741        | 2.9119 | 475  | 0.6680          |
| 0.7613        | 3.0651 | 500  | 0.6659          |
| 0.7733        | 3.2184 | 525  | 0.6654          |
| 0.7605        | 3.3716 | 550  | 0.6623          |
| 0.7538        | 3.5249 | 575  | 0.6606          |
| 0.7626        | 3.6782 | 600  | 0.6596          |
| 0.7573        | 3.8314 | 625  | 0.6577          |
| 0.7469        | 3.9847 | 650  | 0.6556          |
| 0.7524        | 4.1379 | 675  | 0.6537          |
| 0.7342        | 4.2912 | 700  | 0.6491          |
| 0.7305        | 4.4444 | 725  | 0.6511          |
| 0.7433        | 4.5977 | 750  | 0.6486          |
| 0.7438        | 4.7510 | 775  | 0.6487          |
| 0.7505        | 4.9042 | 800  | 0.6481          |
| 0.7354        | 5.0575 | 825  | 0.6450          |
| 0.7354        | 5.2107 | 850  | 0.6439          |
| 0.7333        | 5.3640 | 875  | 0.6462          |
| 0.7246        | 5.5172 | 900  | 0.6444          |
| 0.7289        | 5.6705 | 925  | 0.6417          |
| 0.7436        | 5.8238 | 950  | 0.6474          |
| 0.741         | 5.9770 | 975  | 0.6428          |
| 0.7443        | 6.1303 | 1000 | 0.6468          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.19.1