---
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-combined-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-combined-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: inf
- Wer: 0.5166

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 14.8448       | 0.0762 | 100  | inf             | 1.0079 |
| 6.2506        | 0.1524 | 200  | inf             | 1.0042 |
| 5.5314        | 0.2287 | 300  | inf             | 1.0270 |
| 3.4418        | 0.3049 | 400  | inf             | 0.5906 |
| 1.9396        | 0.3811 | 500  | inf             | 0.5762 |
| 1.698         | 0.4573 | 600  | inf             | 0.5566 |
| 1.5483        | 0.5335 | 700  | inf             | 0.5571 |
| 1.6501        | 0.6098 | 800  | inf             | 0.5487 |
| 1.5528        | 0.6860 | 900  | inf             | 0.5471 |
| 1.5398        | 0.7622 | 1000 | inf             | 0.5479 |
| 1.6413        | 0.8384 | 1100 | inf             | 0.5304 |
| 1.418         | 0.9146 | 1200 | inf             | 0.5283 |
| 1.5625        | 0.9909 | 1300 | inf             | 0.5265 |
| 1.4753        | 1.0671 | 1400 | inf             | 0.5347 |
| 1.616         | 1.1433 | 1500 | inf             | 0.5309 |
| 1.3802        | 1.2195 | 1600 | inf             | 0.5246 |
| 1.4105        | 1.2957 | 1700 | inf             | 0.5197 |
| 1.3793        | 1.3720 | 1800 | inf             | 0.5288 |
| 1.3991        | 1.4482 | 1900 | inf             | 0.5140 |
| 1.5838        | 1.5244 | 2000 | inf             | 0.5239 |
| 1.6283        | 1.6006 | 2100 | inf             | 0.5144 |
| 1.4131        | 1.6768 | 2200 | inf             | 0.5135 |
| 1.388         | 1.7530 | 2300 | inf             | 0.5137 |
| 1.3846        | 1.8293 | 2400 | inf             | 0.5145 |
| 1.497         | 1.9055 | 2500 | inf             | 0.5167 |


### Framework versions

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