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---
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
|