---
license: cc-by-nc-4.0
base_model: facebook/mms-1b
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: results
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: test
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 0.5377405032067094
---

<!-- 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. -->

# results

This model is a fine-tuned version of [facebook/mms-1b](https://huggingface.co/facebook/mms-1b) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3647
- Wer: 0.5377
- Cer: 0.2651

## 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: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 13
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 3.4128        | 1.6495  | 40   | 3.2154          | 1.0    | 1.0    |
| 2.8944        | 3.2990  | 80   | 2.7463          | 0.9896 | 0.9891 |
| 1.5023        | 4.9485  | 120  | 1.4803          | 0.6971 | 0.3166 |
| 1.1458        | 6.5979  | 160  | 1.2789          | 0.5580 | 0.2638 |
| 0.9619        | 8.2474  | 200  | 1.2553          | 0.5639 | 0.2702 |
| 0.8777        | 9.8969  | 240  | 1.2722          | 0.5215 | 0.2633 |
| 0.7732        | 11.5464 | 280  | 1.3647          | 0.5377 | 0.2651 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1