---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_jenny_2000sample
  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_jenny_2000sample

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: 0.3933

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5538        | 0.4444 | 50   | 0.4639          |
| 0.507         | 0.8889 | 100  | 0.4439          |
| 0.4823        | 1.3333 | 150  | 0.4217          |
| 0.4739        | 1.7778 | 200  | 0.4156          |
| 0.4661        | 2.2222 | 250  | 0.4094          |
| 0.4582        | 2.6667 | 300  | 0.4071          |
| 0.439         | 3.1111 | 350  | 0.4024          |
| 0.4499        | 3.5556 | 400  | 0.4038          |
| 0.4379        | 4.0    | 450  | 0.4004          |
| 0.4294        | 4.4444 | 500  | 0.3995          |
| 0.427         | 4.8889 | 550  | 0.3963          |
| 0.4262        | 5.3333 | 600  | 0.3957          |
| 0.4319        | 5.7778 | 650  | 0.3959          |
| 0.4171        | 6.2222 | 700  | 0.3948          |
| 0.4248        | 6.6667 | 750  | 0.3967          |
| 0.4195        | 7.1111 | 800  | 0.3946          |
| 0.4174        | 7.5556 | 850  | 0.3939          |
| 0.4183        | 8.0    | 900  | 0.3945          |
| 0.4107        | 8.4444 | 950  | 0.3934          |
| 0.422         | 8.8889 | 1000 | 0.3933          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1