---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_sr_proj
  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_finetuned_sr_proj

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: 0.4312

## 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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- 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: 200
- training_steps: 1400
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7348        | 0.2093 | 100  | 0.6215          |
| 0.6423        | 0.4186 | 200  | 0.5610          |
| 0.5402        | 0.6279 | 300  | 0.4746          |
| 0.5147        | 0.8373 | 400  | 0.4594          |
| 0.5036        | 1.0466 | 500  | 0.4507          |
| 0.5033        | 1.2559 | 600  | 0.4477          |
| 0.4917        | 1.4652 | 700  | 0.4407          |
| 0.492         | 1.6745 | 800  | 0.4391          |
| 0.481         | 1.8838 | 900  | 0.4387          |
| 0.4826        | 2.0931 | 1000 | 0.4334          |
| 0.4842        | 2.3025 | 1100 | 0.4342          |
| 0.4796        | 2.5118 | 1200 | 0.4325          |
| 0.4735        | 2.7211 | 1300 | 0.4311          |
| 0.4771        | 2.9304 | 1400 | 0.4312          |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1