---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- bigcgen
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-bigcgen-male-30hrs-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-bigcgen-male-30hrs-model

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the BIGCGEN - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4418
- Wer: 0.4513

## 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
- gradient_accumulation_steps: 2
- 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
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 14.8177       | 0.0518 | 100  | 0.9883          | 0.8360 |
| 1.9066        | 0.1035 | 200  | 0.6111          | 0.5658 |
| 1.6259        | 0.1553 | 300  | 0.5919          | 0.5600 |
| 1.5344        | 0.2071 | 400  | 0.5518          | 0.5453 |
| 1.5788        | 0.2589 | 500  | 0.5322          | 0.5417 |
| 1.3816        | 0.3106 | 600  | 0.4890          | 0.5234 |
| 1.3242        | 0.3624 | 700  | 0.4798          | 0.5032 |
| 1.301         | 0.4142 | 800  | 0.4813          | 0.5160 |
| 1.1288        | 0.4660 | 900  | 0.4632          | 0.4895 |
| 1.2779        | 0.5177 | 1000 | 0.4606          | 0.4855 |
| 1.172         | 0.5695 | 1100 | 0.4532          | 0.4835 |
| 1.2388        | 0.6213 | 1200 | 0.4610          | 0.4833 |
| 1.2582        | 0.6731 | 1300 | 0.4502          | 0.4667 |
| 1.1046        | 0.7248 | 1400 | 0.4608          | 0.4696 |
| 1.2732        | 0.7766 | 1500 | 0.4450          | 0.4696 |
| 1.2323        | 0.8284 | 1600 | 0.4495          | 0.4631 |
| 1.282         | 0.8801 | 1700 | 0.4401          | 0.4604 |
| 1.1099        | 0.9319 | 1800 | 0.4440          | 0.4612 |
| 1.1463        | 0.9837 | 1900 | 0.4417          | 0.4689 |
| 1.12          | 1.0352 | 2000 | 0.4408          | 0.4549 |
| 1.1037        | 1.0870 | 2100 | 0.4418          | 0.4513 |


### Framework versions

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