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---
license: apache-2.0
language:
- vi
tags:
- automatic-speech-recognition
- common-voice
- hf-asr-leaderboard
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: xls-asr-vi-40h-1B
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7.0
type: mozilla-foundation/common_voice_7_0
args: vi
metrics:
- name: Test WER (with LM)
type: wer
value: 25.846
- name: Test CER (with LM)
type: cer
value: 12.961
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8.0
type: mozilla-foundation/common_voice_8_0
args: vi
metrics:
- name: Test WER (with LM)
type: wer
value: 31.158
- name: Test CER (with LM)
type: cer
value: 16.179
---
# xls-asr-vi-40h-1B
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on 40 hours of FPT Open Speech Dataset (FOSD) and Common Voice 7.0.
### Benchmark WER result:
| | [VIVOS](https://huggingface.co/datasets/vivos) | [COMMON VOICE 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0) | [COMMON VOICE 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0)
|---|---|---|---|
|without LM| 25.93 | 34.21 |
|with 4-grams LM| 24.11 | 25.84 | 31.158 |
### Benchmark CER result:
| | [VIVOS](https://huggingface.co/datasets/vivos) | [COMMON VOICE 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0) | [COMMON VOICE 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0)
|---|---|---|---|
|without LM| 9.24 | 19.94 |
|with 4-grams LM| 10.37 | 12.96 | 16.179 |
## Evaluation
Please use the eval.py file to run the evaluation
```python
python eval.py --model_id geninhu/xls-asr-vi-40h-1B --dataset mozilla-foundation/common_voice_7_0 --config vi --split test --log_outputs
```
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1500
- num_epochs: 10.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.6222 | 1.85 | 1500 | 5.9479 | 0.5474 |
| 1.1362 | 3.7 | 3000 | 7.9799 | 0.5094 |
| 0.7814 | 5.56 | 4500 | 5.0330 | 0.4724 |
| 0.6281 | 7.41 | 6000 | 2.3484 | 0.5020 |
| 0.5472 | 9.26 | 7500 | 2.2495 | 0.4793 |
| 0.4827 | 11.11 | 9000 | 1.1530 | 0.4768 |
| 0.4327 | 12.96 | 10500 | 1.6160 | 0.4646 |
| 0.3989 | 14.81 | 12000 | 3.2633 | 0.4703 |
| 0.3522 | 16.67 | 13500 | 2.2337 | 0.4708 |
| 0.3201 | 18.52 | 15000 | 3.6879 | 0.4565 |
| 0.2899 | 20.37 | 16500 | 5.4389 | 0.4599 |
| 0.2776 | 22.22 | 18000 | 3.5284 | 0.4537 |
| 0.2574 | 24.07 | 19500 | 2.1759 | 0.4649 |
| 0.2378 | 25.93 | 21000 | 3.3901 | 0.4448 |
| 0.217 | 27.78 | 22500 | 1.1632 | 0.4565 |
| 0.2115 | 29.63 | 24000 | 1.7441 | 0.4232 |
| 0.1959 | 31.48 | 25500 | 3.4992 | 0.4304 |
| 0.187 | 33.33 | 27000 | 3.6163 | 0.4369 |
| 0.1748 | 35.19 | 28500 | 3.6038 | 0.4467 |
| 0.17 | 37.04 | 30000 | 2.9708 | 0.4362 |
| 0.159 | 38.89 | 31500 | 3.2045 | 0.4279 |
| 0.153 | 40.74 | 33000 | 3.2427 | 0.4287 |
| 0.1463 | 42.59 | 34500 | 3.5439 | 0.4270 |
| 0.139 | 44.44 | 36000 | 3.9381 | 0.4150 |
| 0.1352 | 46.3 | 37500 | 4.1744 | 0.4092 |
| 0.1369 | 48.15 | 39000 | 4.2279 | 0.4154 |
| 0.1273 | 50.0 | 40500 | 4.1691 | 0.4133 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
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