---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: ceb_b32_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. -->

# ceb_b32_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: 0.4051

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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 |
|:-------------:|:--------:|:-----:|:---------------:|
| 0.4691        | 9.9010   | 500   | 0.4229          |
| 0.4352        | 19.8020  | 1000  | 0.4041          |
| 0.424         | 29.7030  | 1500  | 0.4032          |
| 0.4091        | 39.6040  | 2000  | 0.4037          |
| 0.4117        | 49.5050  | 2500  | 0.4078          |
| 0.3884        | 59.4059  | 3000  | 0.4005          |
| 0.3826        | 69.3069  | 3500  | 0.4024          |
| 0.3766        | 79.2079  | 4000  | 0.4015          |
| 0.3712        | 89.1089  | 4500  | 0.4025          |
| 0.3571        | 99.0099  | 5000  | 0.4016          |
| 0.3671        | 108.9109 | 5500  | 0.4021          |
| 0.361         | 118.8119 | 6000  | 0.4025          |
| 0.3581        | 128.7129 | 6500  | 0.3989          |
| 0.3476        | 138.6139 | 7000  | 0.4029          |
| 0.3391        | 148.5149 | 7500  | 0.4026          |
| 0.3372        | 158.4158 | 8000  | 0.4037          |
| 0.3345        | 168.3168 | 8500  | 0.4045          |
| 0.3329        | 178.2178 | 9000  | 0.4067          |
| 0.331         | 188.1188 | 9500  | 0.4042          |
| 0.3366        | 198.0198 | 10000 | 0.4051          |
| 0.3276        | 207.9208 | 10500 | 0.4035          |
| 0.3297        | 217.8218 | 11000 | 0.4037          |
| 0.3298        | 227.7228 | 11500 | 0.4031          |
| 0.3241        | 237.6238 | 12000 | 0.4051          |


### Framework versions

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