---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_Bengali_shabdobhedii
  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_Bengali_shabdobhedii

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: 0.5902

## 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: 4
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.7972        | 0.3388 | 100  | 0.7451          |
| 0.7235        | 0.6777 | 200  | 0.6852          |
| 0.6903        | 1.0165 | 300  | 0.6570          |
| 0.6906        | 1.3554 | 400  | 0.6403          |
| 0.676         | 1.6942 | 500  | 0.6299          |
| 0.6851        | 2.0330 | 600  | 0.6257          |
| 0.6583        | 2.3719 | 700  | 0.6170          |
| 0.654         | 2.7107 | 800  | 0.6163          |
| 0.6419        | 3.0496 | 900  | 0.6112          |
| 0.6344        | 3.3884 | 1000 | 0.6055          |
| 0.626         | 3.7272 | 1100 | 0.6002          |
| 0.6203        | 4.0661 | 1200 | 0.5949          |
| 0.6253        | 4.4049 | 1300 | 0.5938          |
| 0.6127        | 4.7438 | 1400 | 0.5894          |
| 0.6104        | 5.0826 | 1500 | 0.5902          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1