sammy786/wav2vec2-xlsr-tatar
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - tt dataset. It achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):
- Loss: 7.66
 - Wer: 7.08
 
Model description
"facebook/wav2vec2-xls-r-1b" was finetuned.
Intended uses & limitations
More information needed
Training and evaluation data
Training data - Common voice Finnish train.tsv, dev.tsv and other.tsv
Training procedure
For creating the train dataset, all possible datasets were appended and 90-10 split was used.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.000045637994662983496
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 13
 - gradient_accumulation_steps: 2
 - total_train_batch_size: 32
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine_with_restarts
 - lr_scheduler_warmup_steps: 500
 - num_epochs: 40
 - mixed_precision_training: Native AMP
 
Training results
| Step | Training Loss | Validation Loss | Wer | 
|---|---|---|---|
| 200 | 4.849400 | 1.874908 | 0.995232 | 
| 400 | 1.105700 | 0.257292 | 0.367658 | 
| 600 | 0.723000 | 0.181150 | 0.250513 | 
| 800 | 0.660600 | 0.167009 | 0.226078 | 
| 1000 | 0.568000 | 0.135090 | 0.177339 | 
| 1200 | 0.721200 | 0.117469 | 0.166413 | 
| 1400 | 0.416300 | 0.115142 | 0.153765 | 
| 1600 | 0.346000 | 0.105782 | 0.153963 | 
| 1800 | 0.279700 | 0.102452 | 0.146149 | 
| 2000 | 0.273800 | 0.095818 | 0.128468 | 
| 2200 | 0.252900 | 0.102302 | 0.133766 | 
| 2400 | 0.255100 | 0.096592 | 0.121316 | 
| 2600 | 0.229600 | 0.091263 | 0.124561 | 
| 2800 | 0.213900 | 0.097748 | 0.125687 | 
| 3000 | 0.210700 | 0.091244 | 0.125422 | 
| 3200 | 0.202600 | 0.084076 | 0.106284 | 
| 3400 | 0.200900 | 0.093809 | 0.113238 | 
| 3600 | 0.192700 | 0.082918 | 0.108139 | 
| 3800 | 0.182000 | 0.084487 | 0.103371 | 
| 4000 | 0.167700 | 0.091847 | 0.104960 | 
| 4200 | 0.183700 | 0.085223 | 0.103040 | 
| 4400 | 0.174400 | 0.083862 | 0.100589 | 
| 4600 | 0.163100 | 0.086493 | 0.099728 | 
| 4800 | 0.162000 | 0.081734 | 0.097543 | 
| 5000 | 0.153600 | 0.077223 | 0.092974 | 
| 5200 | 0.153700 | 0.086217 | 0.090789 | 
| 5400 | 0.140200 | 0.093256 | 0.100457 | 
| 5600 | 0.142900 | 0.086903 | 0.097742 | 
| 5800 | 0.131400 | 0.083068 | 0.095225 | 
| 6000 | 0.126000 | 0.086642 | 0.091252 | 
| 6200 | 0.135300 | 0.083387 | 0.091186 | 
| 6400 | 0.126100 | 0.076479 | 0.086352 | 
| 6600 | 0.127100 | 0.077868 | 0.086153 | 
| 6800 | 0.118000 | 0.083878 | 0.087676 | 
| 7000 | 0.117600 | 0.085779 | 0.091054 | 
| 7200 | 0.113600 | 0.084197 | 0.084233 | 
| 7400 | 0.112000 | 0.078688 | 0.081319 | 
| 7600 | 0.110200 | 0.082534 | 0.086087 | 
| 7800 | 0.106400 | 0.077245 | 0.080988 | 
| 8000 | 0.102300 | 0.077497 | 0.079332 | 
| 8200 | 0.109500 | 0.079083 | 0.088339 | 
| 8400 | 0.095900 | 0.079721 | 0.077809 | 
| 8600 | 0.094700 | 0.079078 | 0.079730 | 
| 8800 | 0.097400 | 0.078785 | 0.079200 | 
| 9000 | 0.093200 | 0.077445 | 0.077015 | 
| 9200 | 0.088700 | 0.078207 | 0.076617 | 
| 9400 | 0.087200 | 0.078982 | 0.076485 | 
| 9600 | 0.089900 | 0.081209 | 0.076021 | 
| 9800 | 0.081900 | 0.078158 | 0.075757 | 
| 10000 | 0.080200 | 0.078074 | 0.074498 | 
| 10200 | 0.085000 | 0.078830 | 0.073373 | 
| 10400 | 0.080400 | 0.078144 | 0.073373 | 
| 10600 | 0.078200 | 0.077163 | 0.073902 | 
| 10800 | 0.080900 | 0.076394 | 0.072446 | 
| 11000 | 0.080700 | 0.075955 | 0.071585 | 
| 11200 | 0.076800 | 0.077031 | 0.072313 | 
| 11400 | 0.076300 | 0.077401 | 0.072777 | 
| 11600 | 0.076700 | 0.076613 | 0.071916 | 
| 11800 | 0.076000 | 0.076672 | 0.071916 | 
| 12000 | 0.077200 | 0.076490 | 0.070989 | 
| 12200 | 0.076200 | 0.076688 | 0.070856 | 
| 12400 | 0.074400 | 0.076780 | 0.071055 | 
| 12600 | 0.076300 | 0.076768 | 0.071320 | 
| 12800 | 0.077600 | 0.076727 | 0.071055 | 
| 13000 | 0.077700 | 0.076714 | 0.071254 | 
Framework versions
- Transformers 4.16.0.dev0
 - Pytorch 1.10.0+cu102
 - Datasets 1.17.1.dev0
 - Tokenizers 0.10.3
 
Evaluation Commands
- To evaluate on 
mozilla-foundation/common_voice_8_0with splittest 
python eval.py --model_id sammy786/wav2vec2-xlsr-tatar --dataset mozilla-foundation/common_voice_8_0 --config tt --split test