---
language:
- nl
license: mit
base_model: microsoft/speecht5_tts
tags:
- tags
- generated_from_trainer
datasets:
- amharic_parallel
model-index:
- name: SpeechT5-TTS-Amh
  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-TTS-Amh

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the alefa_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3722

## 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: 500
- training_steps: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4268        | 3.46  | 1000 | 0.3934          |
| 0.4066        | 6.92  | 2000 | 0.3832          |
| 0.3997        | 10.38 | 3000 | 0.3745          |
| 0.3976        | 13.84 | 4000 | 0.3722          |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3