---
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-15hrs-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-15hrs-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: 0.5205

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 14.809        | 0.1003 | 100  | inf             | 1.0120 |
| 6.0699        | 0.2005 | 200  | inf             | 0.9993 |
| 5.3221        | 0.3008 | 300  | inf             | 1.0347 |
| 4.0785        | 0.4010 | 400  | inf             | 0.7821 |
| 2.0743        | 0.5013 | 500  | inf             | 0.6082 |
| 1.7578        | 0.6015 | 600  | inf             | 0.5732 |
| 1.8081        | 0.7018 | 700  | inf             | 0.5659 |
| 1.7107        | 0.8020 | 800  | inf             | 0.5478 |
| 1.7206        | 0.9023 | 900  | inf             | 0.5489 |
| 1.6957        | 1.0020 | 1000 | inf             | 0.5446 |
| 1.587         | 1.1023 | 1100 | inf             | 0.5380 |
| 1.5794        | 1.2025 | 1200 | inf             | 0.5355 |
| 1.4728        | 1.3028 | 1300 | inf             | 0.5251 |
| 1.5137        | 1.4030 | 1400 | inf             | 0.5380 |
| 1.5073        | 1.5033 | 1500 | inf             | 0.5294 |
| 1.3676        | 1.6035 | 1600 | inf             | 0.5271 |
| 1.5592        | 1.7038 | 1700 | inf             | 0.5240 |
| 1.5091        | 1.8040 | 1800 | inf             | 0.5682 |
| 1.5439        | 1.9043 | 1900 | inf             | 0.5208 |
| 1.4025        | 2.0040 | 2000 | inf             | 0.5276 |
| 1.465         | 2.1043 | 2100 | inf             | 0.5269 |
| 1.4096        | 2.2045 | 2200 | inf             | 0.5346 |
| 1.428         | 2.3048 | 2300 | inf             | 0.5212 |
| 1.3829        | 2.4050 | 2400 | inf             | 0.5217 |
| 1.3048        | 2.5053 | 2500 | inf             | 0.5205 |


### Framework versions

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