---
library_name: transformers
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-genbed-all
  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. -->

# mms-1b-bem-genbed-all

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: 0.2479
- Wer: 0.4062

## 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: 0.0003
- 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        | 0.2747 | 200  | 0.6312          | 0.6736 |
| No log        | 0.5495 | 400  | 0.3199          | 0.4919 |
| 2.9901        | 0.8242 | 600  | 0.3014          | 0.4613 |
| 2.9901        | 1.0989 | 800  | 0.2825          | 0.4433 |
| 0.3968        | 1.3736 | 1000 | 0.2783          | 0.4541 |
| 0.3968        | 1.6484 | 1200 | 0.2732          | 0.4294 |
| 0.3968        | 1.9231 | 1400 | 0.2649          | 0.4244 |
| 0.3766        | 2.1978 | 1600 | 0.2621          | 0.4204 |
| 0.3766        | 2.4725 | 1800 | 0.2628          | 0.4171 |
| 0.3537        | 2.7473 | 2000 | 0.2579          | 0.4187 |
| 0.3537        | 3.0220 | 2200 | 0.2557          | 0.4034 |
| 0.3537        | 3.2967 | 2400 | 0.2524          | 0.4091 |
| 0.3529        | 3.5714 | 2600 | 0.2535          | 0.4061 |
| 0.3529        | 3.8462 | 2800 | 0.2495          | 0.4034 |
| 0.3393        | 4.1209 | 3000 | 0.2494          | 0.4065 |
| 0.3393        | 4.3956 | 3200 | 0.2488          | 0.4066 |
| 0.3393        | 4.6703 | 3400 | 0.2482          | 0.4028 |
| 0.3332        | 4.9451 | 3600 | 0.2479          | 0.4062 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1