---
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-10hrs-model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mms-1b-bigcgen-male-10hrs-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: 0.4413
- Wer: 0.4554

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 12.1631       | 0.1548 | 100  | 1.2139          | 0.8800 |
| 1.7593        | 0.3096 | 200  | 0.6127          | 0.5689 |
| 1.6361        | 0.4644 | 300  | 0.5921          | 0.5732 |
| 1.6146        | 0.6192 | 400  | 0.5587          | 0.5547 |
| 1.3783        | 0.7740 | 500  | 0.5520          | 0.5314 |
| 1.36          | 0.9288 | 600  | 0.5444          | 0.5278 |
| 1.3447        | 1.0836 | 700  | 0.5394          | 0.5126 |
| 1.3265        | 1.2384 | 800  | 0.5085          | 0.5028 |
| 1.2625        | 1.3932 | 900  | 0.4822          | 0.5008 |
| 1.2793        | 1.5480 | 1000 | 0.5092          | 0.5037 |
| 1.266         | 1.7028 | 1100 | 0.4713          | 0.4958 |
| 1.2451        | 1.8576 | 1200 | 0.4544          | 0.4780 |
| 1.3066        | 2.0124 | 1300 | 0.4491          | 0.4737 |
| 1.2102        | 2.1672 | 1400 | 0.4510          | 0.4785 |
| 1.2384        | 2.3220 | 1500 | 0.4534          | 0.4756 |
| 1.2143        | 2.4768 | 1600 | 0.4538          | 0.4734 |
| 1.0998        | 2.6316 | 1700 | 0.4472          | 0.4684 |
| 1.0608        | 2.7864 | 1800 | 0.4533          | 0.4616 |
| 1.1756        | 2.9412 | 1900 | 0.4384          | 0.4614 |
| 1.0873        | 3.0960 | 2000 | 0.4458          | 0.4638 |
| 1.0788        | 3.2508 | 2100 | 0.4400          | 0.4573 |
| 1.1188        | 3.4056 | 2200 | 0.4412          | 0.4650 |
| 1.2589        | 3.5604 | 2300 | 0.4413          | 0.4554 |


### Framework versions

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