---
license: mit
tags:
- generated_from_trainer
datasets:
- fleurs
model-index:
- name: speecht5_finetuned_google_fleurs_greek
  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_google_fleurs_greek

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3419

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5791        | 0.99  | 106  | 0.4965          |
| 0.4962        | 2.0   | 213  | 0.4057          |
| 0.4719        | 3.0   | 320  | 0.3929          |
| 0.4387        | 4.0   | 427  | 0.3793          |
| 0.4366        | 4.99  | 533  | 0.3749          |
| 0.4216        | 6.0   | 640  | 0.3715          |
| 0.4238        | 7.0   | 747  | 0.3663          |
| 0.4199        | 8.0   | 854  | 0.3622          |
| 0.415         | 8.99  | 960  | 0.3595          |
| 0.409         | 10.0  | 1067 | 0.3579          |
| 0.4128        | 11.0  | 1174 | 0.3526          |
| 0.4065        | 12.0  | 1281 | 0.3554          |
| 0.4023        | 12.99 | 1387 | 0.3573          |
| 0.4028        | 14.0  | 1494 | 0.3482          |
| 0.407         | 15.0  | 1601 | 0.3487          |
| 0.4018        | 16.0  | 1708 | 0.3518          |
| 0.3987        | 16.99 | 1814 | 0.3483          |
| 0.3966        | 18.0  | 1921 | 0.3461          |
| 0.3931        | 19.0  | 2028 | 0.3534          |
| 0.3956        | 20.0  | 2135 | 0.3473          |
| 0.396         | 20.99 | 2241 | 0.3451          |
| 0.3963        | 22.0  | 2348 | 0.3435          |
| 0.3928        | 23.0  | 2455 | 0.3468          |
| 0.39          | 24.0  | 2562 | 0.3452          |
| 0.3875        | 24.99 | 2668 | 0.3430          |
| 0.405         | 26.0  | 2775 | 0.3458          |
| 0.3857        | 27.0  | 2882 | 0.3444          |
| 0.3869        | 28.0  | 2989 | 0.3436          |
| 0.3813        | 28.99 | 3095 | 0.3419          |
| 0.3859        | 30.0  | 3202 | 0.3430          |
| 0.3965        | 31.0  | 3309 | 0.3419          |
| 0.3873        | 32.0  | 3416 | 0.3432          |
| 0.3894        | 32.99 | 3522 | 0.3423          |
| 0.3855        | 34.0  | 3629 | 0.3412          |
| 0.3857        | 35.0  | 3736 | 0.3423          |
| 0.3856        | 36.0  | 3843 | 0.3420          |
| 0.3842        | 36.99 | 3949 | 0.3418          |
| 0.3827        | 38.0  | 4056 | 0.3421          |
| 0.389         | 39.0  | 4163 | 0.3423          |
| 0.3881        | 39.72 | 4240 | 0.3419          |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3