---
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-25hrs-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-25hrs-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: 0.5156

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 14.5485       | 0.0611 | 100  | inf             | 1.0039 |
| 6.1502        | 0.1222 | 200  | inf             | 1.0675 |
| 5.1685        | 0.1833 | 300  | inf             | 1.0053 |
| 2.0876        | 0.2443 | 400  | inf             | 0.5857 |
| 1.7116        | 0.3054 | 500  | inf             | 0.5759 |
| 1.6505        | 0.3665 | 600  | inf             | 0.5579 |
| 1.6573        | 0.4276 | 700  | inf             | 0.5471 |
| 1.4679        | 0.4887 | 800  | inf             | 0.5528 |
| 1.4955        | 0.5498 | 900  | inf             | 0.5369 |
| 1.664         | 0.6109 | 1000 | inf             | 0.5328 |
| 1.61          | 0.6720 | 1100 | inf             | 0.5335 |
| 1.6414        | 0.7330 | 1200 | inf             | 0.5293 |
| 1.6321        | 0.7941 | 1300 | inf             | 0.5271 |
| 1.4686        | 0.8552 | 1400 | inf             | 0.5297 |
| 1.5073        | 0.9163 | 1500 | inf             | 0.5326 |
| 1.6164        | 0.9774 | 1600 | inf             | 0.5235 |
| 1.577         | 1.0385 | 1700 | inf             | 0.5238 |
| 1.383         | 1.0996 | 1800 | inf             | 0.5217 |
| 1.4391        | 1.1607 | 1900 | inf             | 0.5292 |
| 1.5327        | 1.2217 | 2000 | inf             | 0.5255 |
| 1.3653        | 1.2828 | 2100 | inf             | 0.5195 |
| 1.4901        | 1.3439 | 2200 | inf             | 0.5187 |
| 1.4263        | 1.4050 | 2300 | inf             | 0.5169 |
| 1.4603        | 1.4661 | 2400 | inf             | 0.5179 |
| 1.4802        | 1.5272 | 2500 | inf             | 0.5155 |


### Framework versions

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