---
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-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-female-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: 0.5260

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 13.9528       | 0.0752 | 100  | inf             | 1.0431 |
| 6.1846        | 0.1505 | 200  | inf             | 1.0030 |
| 5.4651        | 0.2257 | 300  | inf             | 1.0386 |
| 4.4356        | 0.3010 | 400  | inf             | 0.8831 |
| 2.2016        | 0.3762 | 500  | inf             | 0.6218 |
| 1.8013        | 0.4515 | 600  | inf             | 0.5746 |
| 1.7499        | 0.5267 | 700  | inf             | 0.5793 |
| 1.6979        | 0.6020 | 800  | inf             | 0.5501 |
| 1.5567        | 0.6772 | 900  | inf             | 0.5439 |
| 1.6301        | 0.7524 | 1000 | inf             | 0.5355 |
| 1.6362        | 0.8277 | 1100 | inf             | 0.5367 |
| 1.5247        | 0.9029 | 1200 | inf             | 0.5326 |
| 1.4012        | 0.9782 | 1300 | inf             | 0.5346 |
| 1.6397        | 1.0534 | 1400 | inf             | 0.5301 |
| 1.5258        | 1.1287 | 1500 | inf             | 0.5285 |
| 1.4144        | 1.2039 | 1600 | inf             | 0.5244 |
| 1.4363        | 1.2792 | 1700 | inf             | 0.5144 |
| 1.3733        | 1.3544 | 1800 | inf             | 0.5358 |
| 1.4592        | 1.4296 | 1900 | inf             | 0.5598 |
| 1.3499        | 1.5049 | 2000 | inf             | 0.5192 |
| 1.4039        | 1.5801 | 2100 | inf             | 0.5228 |
| 1.4057        | 1.6554 | 2200 | inf             | 0.5289 |
| 1.4961        | 1.7306 | 2300 | inf             | 0.5323 |
| 1.3975        | 1.8059 | 2400 | inf             | 0.5119 |
| 1.4725        | 1.8811 | 2500 | inf             | 0.5260 |


### Framework versions

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