---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_essam1_ar
  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_essam1_ar

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: 0.3612

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.5284        | 0.3742 | 100  | 0.4634          |
| 0.4832        | 0.7484 | 200  | 0.4426          |
| 0.4524        | 1.1225 | 300  | 0.4221          |
| 0.4426        | 1.4967 | 400  | 0.4052          |
| 0.4311        | 1.8709 | 500  | 0.3923          |
| 0.4207        | 2.2451 | 600  | 0.3799          |
| 0.4139        | 2.6193 | 700  | 0.3724          |
| 0.4045        | 2.9935 | 800  | 0.3675          |
| 0.3978        | 3.3676 | 900  | 0.3635          |
| 0.3958        | 3.7418 | 1000 | 0.3612          |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3