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

# zlm_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: 0.3177

## 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: 8
- eval_batch_size: 8
- 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: 2000
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.5277        | 0.4188  | 500  | 0.4806          |
| 0.4582        | 0.8377  | 1000 | 0.4116          |
| 0.4312        | 1.2565  | 1500 | 0.3951          |
| 0.4122        | 1.6754  | 2000 | 0.3768          |
| 0.4002        | 2.0942  | 2500 | 0.3599          |
| 0.3905        | 2.5131  | 3000 | 0.3521          |
| 0.3806        | 2.9319  | 3500 | 0.3445          |
| 0.37          | 3.3508  | 4000 | 0.3474          |
| 0.3736        | 3.7696  | 4500 | 0.3362          |
| 0.3608        | 8.3872  | 5000 | 0.3342          |
| 0.3602        | 9.2249  | 5500 | 0.3258          |
| 0.3561        | 10.0626 | 6000 | 0.3230          |
| 0.3505        | 10.9003 | 6500 | 0.3199          |
| 0.3473        | 11.7380 | 7000 | 0.3193          |
| 0.3523        | 12.5757 | 7500 | 0.3177          |
| 0.3462        | 13.4134 | 8000 | 0.3177          |


### Framework versions

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