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---
language:
- dv
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- dv
- robust-speech-event
- model_for_talk
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: sammy786/wav2vec2-xlsr-dhivehi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: dv
metrics:
- name: Test WER
type: wer
value: 26.91
- name: Test CER
type: cer
value: 4.02
---
# sammy786/wav2vec2-xlsr-dhivehi
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - dv dataset.
It achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):
- Loss: 14.86
- Wer: 29.32
## 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: 8
- eval_batch_size: 16
- seed: 13
- gradient_accumulation_steps: 4
- 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: 30
- mixed_precision_training: Native AMP
### Training results
| Step | Training Loss | Validation Loss | Wer |
|-------|---------------|-----------------|----------|
| 200 | 4.883800 | 3.190218 | 1.000000 |
| 400 | 1.600100 | 0.497887 | 0.726159 |
| 600 | 0.928500 | 0.358781 | 0.603892 |
| 800 | 0.867900 | 0.309132 | 0.570786 |
| 1000 | 0.743100 | 0.309116 | 0.552954 |
| 1200 | 0.725100 | 0.266839 | 0.538378 |
| 1400 | 0.786200 | 0.259797 | 0.535897 |
| 1600 | 0.655700 | 0.245691 | 0.517290 |
| 1800 | 0.650500 | 0.246957 | 0.516204 |
| 2000 | 0.685500 | 0.234808 | 0.516204 |
| 2200 | 0.487100 | 0.228409 | 0.507753 |
| 2400 | 0.401300 | 0.221087 | 0.495968 |
| 2600 | 0.359300 | 0.212476 | 0.489301 |
| 2800 | 0.347300 | 0.204848 | 0.487750 |
| 3000 | 0.327000 | 0.203163 | 0.478756 |
| 3200 | 0.337100 | 0.210235 | 0.487595 |
| 3400 | 0.308900 | 0.201471 | 0.491316 |
| 3600 | 0.292600 | 0.192437 | 0.476120 |
| 3800 | 0.289600 | 0.198398 | 0.468445 |
| 4000 | 0.290200 | 0.193484 | 0.467204 |
| 4200 | 0.272600 | 0.193999 | 0.470150 |
| 4400 | 0.266700 | 0.187384 | 0.460769 |
| 4600 | 0.253800 | 0.187279 | 0.476663 |
| 4800 | 0.266400 | 0.197395 | 0.466817 |
| 5000 | 0.258000 | 0.188920 | 0.456660 |
| 5200 | 0.237200 | 0.180770 | 0.457358 |
| 5400 | 0.237900 | 0.178149 | 0.448287 |
| 5600 | 0.232600 | 0.179827 | 0.461002 |
| 5800 | 0.228500 | 0.182142 | 0.445185 |
| 6000 | 0.221000 | 0.173619 | 0.440688 |
| 6200 | 0.219500 | 0.172291 | 0.442859 |
| 6400 | 0.219400 | 0.173339 | 0.430609 |
| 6600 | 0.201900 | 0.177552 | 0.426423 |
| 6800 | 0.199000 | 0.173157 | 0.429834 |
| 7000 | 0.200000 | 0.166503 | 0.423709 |
| 7200 | 0.194600 | 0.171812 | 0.429834 |
| 7400 | 0.192100 | 0.164989 | 0.420530 |
| 7600 | 0.185000 | 0.168355 | 0.418825 |
| 7800 | 0.175100 | 0.168128 | 0.419290 |
| 8000 | 0.173500 | 0.167959 | 0.424950 |
| 8200 | 0.172200 | 0.173643 | 0.414793 |
| 8400 | 0.164200 | 0.167020 | 0.406342 |
| 8600 | 0.170800 | 0.168050 | 0.405334 |
| 8800 | 0.157900 | 0.164290 | 0.396573 |
| 9000 | 0.159900 | 0.163188 | 0.397426 |
| 9200 | 0.151700 | 0.164370 | 0.390991 |
| 9400 | 0.146600 | 0.165053 | 0.392852 |
| 9600 | 0.142200 | 0.164939 | 0.391844 |
| 9800 | 0.148300 | 0.164422 | 0.385719 |
| 10000 | 0.136200 | 0.166569 | 0.385951 |
| 10200 | 0.140700 | 0.161377 | 0.379594 |
| 10400 | 0.133300 | 0.165194 | 0.378276 |
| 10600 | 0.131300 | 0.164328 | 0.369205 |
| 10800 | 0.135500 | 0.160254 | 0.373236 |
| 11000 | 0.121100 | 0.163522 | 0.372693 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.10.3
#### Evaluation Commands
1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test`
```bash
python eval.py --model_id sammy786/wav2vec2-xlsr-dhivehi --dataset mozilla-foundation/common_voice_8_0 --config dv --split test
``` |