---
language:
- vi
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- ducha07/audio_HTV_thoisu
metrics:
- wer
model-index:
- name: ASR-test-1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: HTV news
      type: ducha07/audio_HTV_thoisu
    metrics:
    - name: Wer
      type: wer
      value: 0.2882930019620667
---

<!-- 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. -->

# ASR-test-1

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the HTV news dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5663
- Wer: 0.2883

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.772         | 0.92  | 100  | 0.8456          | 0.4411 |
| 1.1042        | 1.83  | 200  | 0.7041          | 0.4076 |
| 0.9814        | 2.75  | 300  | 0.7243          | 0.3782 |
| 0.9096        | 3.67  | 400  | 0.6771          | 0.3655 |
| 0.8823        | 4.59  | 500  | 0.6265          | 0.3627 |
| 0.8435        | 5.5   | 600  | 0.6200          | 0.3543 |
| 0.8157        | 6.42  | 700  | 0.6414          | 0.3417 |
| 0.822         | 7.34  | 800  | 0.5872          | 0.3431 |
| 0.7852        | 8.26  | 900  | 0.6012          | 0.3387 |
| 0.7533        | 9.17  | 1000 | 0.6023          | 0.3256 |
| 0.7609        | 10.09 | 1100 | 0.5837          | 0.3444 |
| 0.7568        | 11.01 | 1200 | 0.5791          | 0.3311 |
| 0.7091        | 11.93 | 1300 | 0.6227          | 0.3206 |
| 0.7098        | 12.84 | 1400 | 0.5766          | 0.3266 |
| 0.7006        | 13.76 | 1500 | 0.6084          | 0.3117 |
| 0.6673        | 14.68 | 1600 | 0.5857          | 0.3120 |
| 0.6832        | 15.6  | 1700 | 0.5754          | 0.3338 |
| 0.6646        | 16.51 | 1800 | 0.5963          | 0.3117 |
| 0.6524        | 17.43 | 1900 | 0.5816          | 0.3137 |
| 0.6385        | 18.35 | 2000 | 0.5691          | 0.3257 |
| 0.6433        | 19.27 | 2100 | 0.5929          | 0.3105 |
| 0.6129        | 20.18 | 2200 | 0.5709          | 0.3067 |
| 0.624         | 21.1  | 2300 | 0.5686          | 0.3168 |
| 0.6128        | 22.02 | 2400 | 0.5867          | 0.3080 |
| 0.584         | 22.94 | 2500 | 0.5680          | 0.3101 |
| 0.5956        | 23.85 | 2600 | 0.5611          | 0.3023 |
| 0.5825        | 24.77 | 2700 | 0.5821          | 0.2999 |
| 0.56          | 25.69 | 2800 | 0.5622          | 0.3012 |
| 0.56          | 26.61 | 2900 | 0.5590          | 0.3053 |
| 0.5523        | 27.52 | 3000 | 0.5758          | 0.2967 |
| 0.5335        | 28.44 | 3100 | 0.5649          | 0.3090 |
| 0.5686        | 29.36 | 3200 | 0.5703          | 0.2931 |
| 0.5488        | 30.28 | 3300 | 0.5709          | 0.2921 |
| 0.5249        | 31.19 | 3400 | 0.5646          | 0.2973 |
| 0.5278        | 32.11 | 3500 | 0.5628          | 0.2933 |
| 0.5252        | 33.03 | 3600 | 0.5663          | 0.2927 |
| 0.5092        | 33.94 | 3700 | 0.5618          | 0.2922 |
| 0.5099        | 34.86 | 3800 | 0.5616          | 0.2954 |
| 0.5031        | 35.78 | 3900 | 0.5670          | 0.2913 |
| 0.4959        | 36.7  | 4000 | 0.5679          | 0.2923 |
| 0.4936        | 37.61 | 4100 | 0.5675          | 0.2912 |
| 0.5012        | 38.53 | 4200 | 0.5661          | 0.2897 |
| 0.4819        | 39.45 | 4300 | 0.5663          | 0.2883 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0