---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_binisha
  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_binisha

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: 0.6198

## 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: 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: 100
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch     | Step | Validation Loss |
|:-------------:|:---------:|:----:|:---------------:|
| 0.5825        | 88.8889   | 100  | 0.5775          |
| 0.4984        | 177.7778  | 200  | 0.6064          |
| 0.4252        | 266.6667  | 300  | 0.5800          |
| 0.3997        | 355.5556  | 400  | 0.5745          |
| 0.366         | 444.4444  | 500  | 0.5863          |
| 0.3521        | 533.3333  | 600  | 0.5969          |
| 0.3308        | 622.2222  | 700  | 0.5716          |
| 0.32          | 711.1111  | 800  | 0.5757          |
| 0.3088        | 800.0     | 900  | 0.6095          |
| 0.3006        | 888.8889  | 1000 | 0.6352          |
| 0.2911        | 977.7778  | 1100 | 0.6207          |
| 0.2849        | 1066.6667 | 1200 | 0.6181          |
| 0.2869        | 1155.5556 | 1300 | 0.6321          |
| 0.2853        | 1244.4444 | 1400 | 0.6271          |
| 0.285         | 1333.3333 | 1500 | 0.6198          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1