---
language:
- ml
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_16_0
- mms
- generated_from_trainer
datasets:
- common_voice_16_0
metrics:
- wer
model-index:
- name: breeze-listen-w2v2-ml
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: MOZILLA-FOUNDATION/COMMON_VOICE_16_0 - ML
      type: common_voice_16_0
      config: ml
      split: test
      args: 'Config: ml, Training split: train+validation, Eval split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.5348997926744989
---

<!-- 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. -->

# breeze-listen-w2v2-ml

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the MOZILLA-FOUNDATION/COMMON_VOICE_16_0 - ML dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2666
- Wer: 0.5349

## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 0.41  | 200  | 5.4728          | 1.0757 |
| No log        | 0.81  | 400  | 5.1274          | 1.0038 |
| 6.5037        | 1.22  | 600  | 0.6167          | 0.8131 |
| 6.5037        | 1.63  | 800  | 0.3284          | 0.5829 |
| 1.0482        | 2.03  | 1000 | 0.3169          | 0.5667 |
| 1.0482        | 2.44  | 1200 | 0.2876          | 0.5425 |
| 1.0482        | 2.85  | 1400 | 0.2847          | 0.5522 |
| 0.4314        | 3.25  | 1600 | 0.2746          | 0.5394 |
| 0.4314        | 3.66  | 1800 | 0.2698          | 0.5346 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1