---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: zlm_b64_le4_s12000
  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_s12000

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: 0.3114

## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 12000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.5487        | 0.4188  | 500   | 0.4746          |
| 0.483         | 0.8375  | 1000  | 0.4227          |
| 0.432         | 1.2563  | 1500  | 0.3983          |
| 0.429         | 1.6750  | 2000  | 0.3953          |
| 0.4168        | 2.0938  | 2500  | 0.3701          |
| 0.4021        | 2.5126  | 3000  | 0.3613          |
| 0.3925        | 2.9313  | 3500  | 0.3509          |
| 0.3839        | 3.3501  | 4000  | 0.3506          |
| 0.3798        | 3.7688  | 4500  | 0.3423          |
| 0.3693        | 4.1876  | 5000  | 0.3375          |
| 0.3712        | 4.6064  | 5500  | 0.3367          |
| 0.3668        | 5.0251  | 6000  | 0.3316          |
| 0.3635        | 5.4439  | 6500  | 0.3291          |
| 0.3543        | 5.8626  | 7000  | 0.3250          |
| 0.3526        | 6.2814  | 7500  | 0.3221          |
| 0.3525        | 6.7002  | 8000  | 0.3218          |
| 0.3513        | 7.1189  | 8500  | 0.3182          |
| 0.346         | 7.5377  | 9000  | 0.3163          |
| 0.3448        | 7.9564  | 9500  | 0.3162          |
| 0.3563        | 8.3752  | 10000 | 0.3145          |
| 0.3449        | 8.7940  | 10500 | 0.3126          |
| 0.3436        | 9.2127  | 11000 | 0.3128          |
| 0.3413        | 9.6315  | 11500 | 0.3121          |
| 0.3397        | 10.0503 | 12000 | 0.3114          |


### Framework versions

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