---
library_name: transformers
license: mit
base_model: maghrane/speecht5_finetuned_marar1000
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_marar2000
  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_marar2000

This model is a fine-tuned version of [maghrane/speecht5_finetuned_marar1000](https://huggingface.co/maghrane/speecht5_finetuned_marar1000) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4801

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- 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: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.528         | 0.7976  | 100  | 0.5440          |
| 0.5453        | 1.5952  | 200  | 0.5655          |
| 0.5395        | 2.3928  | 300  | 0.5418          |
| 0.5421        | 3.1904  | 400  | 0.5570          |
| 0.5384        | 3.9880  | 500  | 0.5324          |
| 0.5447        | 4.7856  | 600  | 0.5454          |
| 0.5343        | 5.5833  | 700  | 0.5220          |
| 0.5165        | 6.3809  | 800  | 0.5269          |
| 0.5171        | 7.1785  | 900  | 0.5223          |
| 0.507         | 7.9761  | 1000 | 0.5227          |
| 0.5021        | 8.7737  | 1100 | 0.5052          |
| 0.4982        | 9.5713  | 1200 | 0.5081          |
| 0.488         | 10.3689 | 1300 | 0.5026          |
| 0.4787        | 11.1665 | 1400 | 0.4902          |
| 0.4849        | 11.9641 | 1500 | 0.4936          |
| 0.4778        | 12.7617 | 1600 | 0.4934          |
| 0.4646        | 13.5593 | 1700 | 0.4858          |
| 0.4615        | 14.3569 | 1800 | 0.4894          |
| 0.4716        | 15.1545 | 1900 | 0.4832          |
| 0.4607        | 15.9521 | 2000 | 0.4801          |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3