---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: zlm_b32_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. -->

# zlm_b32_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: 0.3854

## 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: 32
- 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: 8050
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7532        | 0.2094 | 500  | 0.6165          |
| 0.6399        | 0.4188 | 1000 | 0.5227          |
| 0.5333        | 0.6281 | 1500 | 0.4723          |
| 0.5159        | 0.8375 | 2000 | 0.4493          |
| 0.4795        | 1.0469 | 2500 | 0.4283          |
| 0.4821        | 1.2563 | 3000 | 0.4274          |
| 0.4563        | 1.4657 | 3500 | 0.4122          |
| 0.4428        | 1.6750 | 4000 | 0.4040          |
| 0.4604        | 1.8844 | 4500 | 0.4010          |
| 0.4545        | 2.0938 | 5000 | 0.3986          |
| 0.445         | 2.3032 | 5500 | 0.3939          |
| 0.4279        | 2.5126 | 6000 | 0.3892          |
| 0.4451        | 2.7219 | 6500 | 0.3893          |
| 0.4243        | 2.9313 | 7000 | 0.3868          |
| 0.4356        | 3.1407 | 7500 | 0.3857          |
| 0.4429        | 3.3501 | 8000 | 0.3854          |


### Framework versions

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