---
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-15hrs-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-15hrs-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: 0.4756
- Wer: 0.4703

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 14.7965       | 0.1033 | 100  | 3.5227          | 1.0007 |
| 6.2688        | 0.2066 | 200  | 2.7700          | 1.0325 |
| 3.6179        | 0.3099 | 300  | 0.7532          | 0.6069 |
| 1.7779        | 0.4132 | 400  | 0.6508          | 0.5821 |
| 1.5595        | 0.5165 | 500  | 0.6249          | 0.5578 |
| 1.5884        | 0.6198 | 600  | 0.6142          | 0.5283 |
| 1.5532        | 0.7231 | 700  | 0.5929          | 0.5172 |
| 1.4021        | 0.8264 | 800  | 0.5996          | 0.5182 |
| 1.507         | 0.9298 | 900  | 0.5824          | 0.5121 |
| 1.5374        | 1.0331 | 1000 | 0.5615          | 0.5061 |
| 1.4139        | 1.1364 | 1100 | 0.5456          | 0.5066 |
| 1.4472        | 1.2397 | 1200 | 0.5177          | 0.4874 |
| 1.2958        | 1.3430 | 1300 | 0.5022          | 0.4871 |
| 1.3292        | 1.4463 | 1400 | 0.4984          | 0.4871 |
| 1.2062        | 1.5496 | 1500 | 0.4886          | 0.4799 |
| 1.1623        | 1.6529 | 1600 | 0.4811          | 0.4823 |
| 1.2759        | 1.7562 | 1700 | 0.4735          | 0.4677 |
| 1.1852        | 1.8595 | 1800 | 0.4986          | 0.4669 |
| 1.0712        | 1.9628 | 1900 | 0.5045          | 0.4845 |
| 1.2023        | 2.0661 | 2000 | 0.4755          | 0.4782 |
| 1.2275        | 2.1694 | 2100 | 0.4756          | 0.4705 |


### Framework versions

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