---
license: mit
base_model: guilhermebastos96/speecht5_finetuned_sip_ai_v2
tags:
- generated_from_trainer
datasets:
- multilingual_librispeech
model-index:
- name: speecht5_finetuned_sip_ai_v3
  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_sip_ai_v3

This model is a fine-tuned version of [guilhermebastos96/speecht5_finetuned_sip_ai_v2](https://huggingface.co/guilhermebastos96/speecht5_finetuned_sip_ai_v2) on the multilingual_librispeech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3439

## 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.3996        | 1.68  | 1000  | 0.3638          |
| 0.3885        | 3.35  | 2000  | 0.3554          |
| 0.3785        | 5.03  | 3000  | 0.3508          |
| 0.3764        | 6.71  | 4000  | 0.3488          |
| 0.3732        | 8.38  | 5000  | 0.3485          |
| 0.3806        | 10.06 | 6000  | 0.3460          |
| 0.3739        | 11.74 | 7000  | 0.3454          |
| 0.3703        | 13.41 | 8000  | 0.3458          |
| 0.3732        | 15.09 | 9000  | 0.3445          |
| 0.3695        | 16.76 | 10000 | 0.3439          |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2