xls-asr-vi-40h-1B
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on 40 hours of FPT Open Speech Dataset (FOSD) and Common Voice 7.0.
Benchmark WER result:
| VIVOS | COMMON VOICE 7.0 | COMMON VOICE 8.0 | |
|---|---|---|---|
| without LM | 25.93 | 34.21 | |
| with 4-grams LM | 24.11 | 25.84 | 31.158 | 
Benchmark CER result:
| VIVOS | COMMON VOICE 7.0 | 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 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