---
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-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-combined-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: 0.5077

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 14.5866       | 0.0509 | 100  | inf             | 1.0167 |
| 6.2466        | 0.1018 | 200  | inf             | 1.0019 |
| 5.4142        | 0.1526 | 300  | inf             | 0.9912 |
| 2.1374        | 0.2035 | 400  | inf             | 0.5952 |
| 1.741         | 0.2544 | 500  | inf             | 0.5641 |
| 1.6543        | 0.3053 | 600  | inf             | 0.5607 |
| 1.6579        | 0.3561 | 700  | inf             | 0.5585 |
| 1.676         | 0.4070 | 800  | inf             | 0.5475 |
| 1.5245        | 0.4579 | 900  | inf             | 0.5410 |
| 1.6324        | 0.5088 | 1000 | inf             | 0.5278 |
| 1.6878        | 0.5597 | 1100 | inf             | 0.5244 |
| 1.4994        | 0.6105 | 1200 | inf             | 0.5259 |
| 1.544         | 0.6614 | 1300 | inf             | 0.5211 |
| 1.5796        | 0.7123 | 1400 | inf             | 0.5244 |
| 1.3625        | 0.7632 | 1500 | inf             | 0.5235 |
| 1.4826        | 0.8140 | 1600 | inf             | 0.5165 |
| 1.4439        | 0.8649 | 1700 | inf             | 0.5227 |
| 1.4778        | 0.9158 | 1800 | inf             | 0.5148 |
| 1.389         | 0.9667 | 1900 | inf             | 0.5130 |
| 1.3863        | 1.0173 | 2000 | inf             | 0.5177 |
| 1.516         | 1.0682 | 2100 | inf             | 0.5082 |
| 1.474         | 1.1191 | 2200 | inf             | 0.5106 |
| 1.465         | 1.1699 | 2300 | inf             | 0.5077 |
| 1.484         | 1.2208 | 2400 | inf             | 0.5090 |
| 1.3942        | 1.2717 | 2500 | inf             | 0.5079 |


### Framework versions

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