---
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-20hrs-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-20hrs-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: 0.4819
- Wer: 0.4453

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 16.6224       | 0.0779 | 100  | 3.4136          | 1.0050 |
| 6.3668        | 0.1557 | 200  | 2.9155          | 1.0462 |
| 4.9805        | 0.2336 | 300  | 0.8884          | 0.6814 |
| 1.9813        | 0.3114 | 400  | 0.6719          | 0.5626 |
| 1.7501        | 0.3893 | 500  | 0.6440          | 0.5494 |
| 1.5396        | 0.4671 | 600  | 0.6134          | 0.5319 |
| 1.498         | 0.5450 | 700  | 0.6120          | 0.5162 |
| 1.475         | 0.6228 | 800  | 0.6036          | 0.5167 |
| 1.4093        | 0.7007 | 900  | 0.6058          | 0.5057 |
| 1.4896        | 0.7785 | 1000 | 0.6087          | 0.5121 |
| 1.3766        | 0.8564 | 1100 | 0.5707          | 0.5001 |
| 1.5787        | 0.9342 | 1200 | 0.5645          | 0.4907 |
| 1.5263        | 1.0117 | 1300 | 0.5231          | 0.4766 |
| 1.3527        | 1.0895 | 1400 | 0.5119          | 0.4780 |
| 1.3688        | 1.1674 | 1500 | 0.5115          | 0.4850 |
| 1.2191        | 1.2452 | 1600 | 0.5105          | 0.4746 |
| 1.1941        | 1.3231 | 1700 | 0.4952          | 0.4698 |
| 1.2454        | 1.4009 | 1800 | 0.4935          | 0.4780 |
| 1.2166        | 1.4788 | 1900 | 0.4931          | 0.4742 |
| 1.2543        | 1.5566 | 2000 | 0.4945          | 0.4609 |
| 1.1682        | 1.6345 | 2100 | 0.5006          | 0.4626 |
| 1.1835        | 1.7123 | 2200 | 0.4783          | 0.4655 |
| 1.1652        | 1.7902 | 2300 | 0.4827          | 0.4520 |
| 1.2329        | 1.8680 | 2400 | 0.4889          | 0.4549 |
| 1.1871        | 1.9459 | 2500 | 0.4753          | 0.4547 |
| 1.1469        | 2.0234 | 2600 | 0.4830          | 0.4532 |
| 1.1214        | 2.1012 | 2700 | 0.4740          | 0.4508 |
| 1.1185        | 2.1791 | 2800 | 0.4788          | 0.4516 |
| 1.1788        | 2.2569 | 2900 | 0.4865          | 0.4571 |
| 1.1214        | 2.3348 | 3000 | 0.4726          | 0.4434 |
| 1.1868        | 2.4126 | 3100 | 0.4846          | 0.4528 |
| 1.2368        | 2.4905 | 3200 | 0.4775          | 0.4335 |
| 1.214         | 2.5683 | 3300 | 0.4925          | 0.4422 |
| 1.1078        | 2.6462 | 3400 | 0.4820          | 0.4455 |


### Framework versions

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