---
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-female-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-female-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: inf
- Wer: 0.5369

## 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
- training_steps: 2500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 14.2597       | 0.0501 | 100  | inf             | 1.0025 |
| 6.2197        | 0.1002 | 200  | inf             | 0.9946 |
| 5.2752        | 0.1503 | 300  | inf             | 1.0316 |
| 2.3626        | 0.2004 | 400  | inf             | 0.5998 |
| 1.7448        | 0.2504 | 500  | inf             | 0.5814 |
| 1.6955        | 0.3005 | 600  | inf             | 0.5709 |
| 1.6841        | 0.3506 | 700  | inf             | 0.5596 |
| 1.693         | 0.4007 | 800  | inf             | 0.5639 |
| 1.688         | 0.4508 | 900  | inf             | 0.5555 |
| 1.5718        | 0.5009 | 1000 | inf             | 0.5476 |
| 1.5855        | 0.5510 | 1100 | inf             | 0.5482 |
| 1.4783        | 0.6011 | 1200 | inf             | 0.5471 |
| 1.5198        | 0.6511 | 1300 | inf             | 0.5476 |
| 1.4941        | 0.7012 | 1400 | inf             | 0.5469 |
| 1.5916        | 0.7513 | 1500 | inf             | 0.5426 |
| 1.4683        | 0.8014 | 1600 | inf             | 0.5460 |
| 1.486         | 0.8515 | 1700 | inf             | 0.5528 |
| 1.4353        | 0.9016 | 1800 | inf             | 0.5435 |
| 1.6166        | 0.9517 | 1900 | inf             | 0.5541 |
| 1.531         | 1.0015 | 2000 | inf             | 0.5535 |
| 1.5441        | 1.0516 | 2100 | inf             | 0.5478 |
| 1.3459        | 1.1017 | 2200 | inf             | 0.5274 |
| 1.357         | 1.1518 | 2300 | inf             | 0.5269 |
| 1.4464        | 1.2019 | 2400 | inf             | 0.5226 |
| 1.4326        | 1.2519 | 2500 | inf             | 0.5369 |


### Framework versions

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