---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- BembaSpeech
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-bem-male-sv
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/cicasote/huggingface/runs/x8tbh9an)
# mms-1b-bem-male-sv

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the BEMBASPEECH - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1409
- Wer: 0.3498

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 0.2183 | 200  | 0.1927          | 0.4257 |
| No log        | 0.4367 | 400  | 0.1713          | 0.3885 |
| 2.0358        | 0.6550 | 600  | 0.1760          | 0.3907 |
| 2.0358        | 0.8734 | 800  | 0.1819          | 0.4143 |
| 0.519         | 1.0917 | 1000 | 0.1611          | 0.3869 |
| 0.519         | 1.3100 | 1200 | 0.1550          | 0.3736 |
| 0.519         | 1.5284 | 1400 | 0.1538          | 0.3771 |
| 0.4764        | 1.7467 | 1600 | 0.1744          | 0.4176 |
| 0.4764        | 1.9651 | 1800 | 0.1598          | 0.3884 |
| 0.4501        | 2.1834 | 2000 | 0.1507          | 0.3577 |
| 0.4501        | 2.4017 | 2200 | 0.1535          | 0.3763 |
| 0.4501        | 2.6201 | 2400 | 0.1502          | 0.3649 |
| 0.4422        | 2.8384 | 2600 | 0.1457          | 0.3502 |
| 0.4422        | 3.0568 | 2800 | 0.1485          | 0.3580 |
| 0.4217        | 3.2751 | 3000 | 0.1480          | 0.3547 |
| 0.4217        | 3.4934 | 3200 | 0.1498          | 0.3666 |
| 0.4217        | 3.7118 | 3400 | 0.1458          | 0.3494 |
| 0.4144        | 3.9301 | 3600 | 0.1427          | 0.3574 |
| 0.4144        | 4.1485 | 3800 | 0.1445          | 0.3594 |
| 0.3926        | 4.3668 | 4000 | 0.1462          | 0.3666 |
| 0.3926        | 4.5852 | 4200 | 0.1432          | 0.3527 |
| 0.3926        | 4.8035 | 4400 | 0.1409          | 0.3498 |


### Framework versions

- Transformers 4.43.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1