---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- bemgen
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-bemgen-balanced-model
  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-bemgen-balanced-model

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the BEMGEN - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2753
- Wer: 0.4201

## 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: 4
- eval_batch_size: 4
- seed: 42
- 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
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 6.8327        | 0.1031 | 100  | 0.8480          | 0.7889 |
| 0.5906        | 0.2062 | 200  | 0.3704          | 0.5819 |
| 0.4809        | 0.3093 | 300  | 0.3327          | 0.5039 |
| 0.4495        | 0.4124 | 400  | 0.3172          | 0.4894 |
| 0.4266        | 0.5155 | 500  | 0.3102          | 0.4632 |
| 0.4167        | 0.6186 | 600  | 0.3075          | 0.4716 |
| 0.4151        | 0.7216 | 700  | 0.2996          | 0.4829 |
| 0.3955        | 0.8247 | 800  | 0.2985          | 0.4712 |
| 0.3802        | 0.9278 | 900  | 0.2960          | 0.4926 |
| 0.392         | 1.0309 | 1000 | 0.2839          | 0.4374 |
| 0.375         | 1.1340 | 1100 | 0.2837          | 0.4318 |
| 0.3885        | 1.2371 | 1200 | 0.2812          | 0.4257 |
| 0.3824        | 1.3402 | 1300 | 0.2825          | 0.4255 |
| 0.3906        | 1.4433 | 1400 | 0.2794          | 0.4290 |
| 0.3465        | 1.5464 | 1500 | 0.2807          | 0.4283 |
| 0.3564        | 1.6495 | 1600 | 0.2773          | 0.4238 |
| 0.3617        | 1.7526 | 1700 | 0.2750          | 0.4452 |
| 0.3808        | 1.8557 | 1800 | 0.2783          | 0.4229 |
| 0.3661        | 1.9588 | 1900 | 0.2761          | 0.4517 |
| 0.3952        | 2.0619 | 2000 | 0.2753          | 0.4201 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0