---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- nyagen
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-nyagen-balanced-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-nyagen-balanced-model

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the NYAGEN - NYA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1803
- Wer: 0.2549

## 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
- 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
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 7.181         | 0.2762 | 100  | 0.6055          | 0.5247 |
| 0.5071        | 0.5525 | 200  | 0.2452          | 0.3594 |
| 0.3791        | 0.8287 | 300  | 0.2159          | 0.3232 |
| 0.3464        | 1.1050 | 400  | 0.2059          | 0.3047 |
| 0.3326        | 1.3812 | 500  | 0.1919          | 0.2943 |
| 0.322         | 1.6575 | 600  | 0.1868          | 0.2861 |
| 0.3025        | 1.9337 | 700  | 0.1850          | 0.2902 |
| 0.2939        | 2.2099 | 800  | 0.1777          | 0.2698 |
| 0.2971        | 2.4862 | 900  | 0.1716          | 0.2675 |
| 0.2787        | 2.7624 | 1000 | 0.1750          | 0.2716 |
| 0.32          | 3.0387 | 1100 | 0.1725          | 0.2734 |
| 0.2738        | 3.3149 | 1200 | 0.1803          | 0.2544 |


### Framework versions

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