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---
language:
- lt
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- fi
- robust-speech-event
- model_for_talk
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: sammy786/wav2vec2-xlsr-lithuanian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: fi
metrics:
- name: Test WER
type: wer
value: 39.10
- name: Test CER
type: cer
value: 11.38
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: lt
metrics:
- name: Test WER
type: wer
value: 39.10
- name: Test CER
type: cer
value: 11.38
---
# sammy786/wav2vec2-xlsr-lithuanian
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 - lt dataset.
It achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):
- Loss: 13.1811
- Wer: 24.2570
## 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: 40
- mixed_precision_training: Native AMP
### Training results
| Step | Training Loss | Validation Loss | Wer |
|:-----:|:-------------:|:---------------:|:--------:|
| 200 | 5.718700 | 2.897032 | 1.000000 |
| 400 | 1.340000 | 0.309548 | 0.507284 |
| 600 | 0.799100 | 0.220205 | 0.402098 |
| 800 | 0.494400 | 0.185093 | 0.352855 |
| 1000 | 0.370800 | 0.165869 | 0.334207 |
| 1200 | 0.312500 | 0.159801 | 0.324009 |
| 1400 | 0.276100 | 0.148066 | 0.321678 |
| 1600 | 0.250100 | 0.153748 | 0.311626 |
| 1800 | 0.226400 | 0.147437 | 0.302885 |
| 2000 | 0.206900 | 0.141176 | 0.296037 |
| 2200 | 0.189900 | 0.142161 | 0.288170 |
| 2400 | 0.192100 | 0.138029 | 0.286568 |
| 2600 | 0.175600 | 0.139496 | 0.283654 |
| 2800 | 0.156900 | 0.138609 | 0.283217 |
| 3000 | 0.149400 | 0.140468 | 0.281906 |
| 3200 | 0.144600 | 0.132472 | 0.278263 |
| 3400 | 0.144100 | 0.141028 | 0.277535 |
| 3600 | 0.133000 | 0.134287 | 0.275495 |
| 3800 | 0.126600 | 0.149136 | 0.277681 |
| 4000 | 0.123500 | 0.132180 | 0.266463 |
| 4200 | 0.113000 | 0.137942 | 0.268211 |
| 4400 | 0.111700 | 0.140038 | 0.272873 |
| 4600 | 0.108600 | 0.136756 | 0.264132 |
| 4800 | 0.103600 | 0.137541 | 0.263403 |
| 5000 | 0.098000 | 0.140435 | 0.264860 |
| 5200 | 0.095800 | 0.136950 | 0.262383 |
| 5400 | 0.094000 | 0.128214 | 0.263986 |
| 5600 | 0.085300 | 0.125024 | 0.259761 |
| 5800 | 0.078900 | 0.128575 | 0.260198 |
| 6000 | 0.083300 | 0.135496 | 0.258887 |
| 6200 | 0.078800 | 0.131706 | 0.259178 |
| 6400 | 0.073800 | 0.128451 | 0.255390 |
| 6600 | 0.072600 | 0.131245 | 0.252768 |
| 6800 | 0.073300 | 0.131525 | 0.249417 |
| 7000 | 0.069000 | 0.128627 | 0.255536 |
| 7200 | 0.064400 | 0.127767 | 0.250583 |
| 7400 | 0.065400 | 0.129557 | 0.247815 |
| 7600 | 0.061200 | 0.129734 | 0.250146 |
| 7800 | 0.059100 | 0.135124 | 0.249709 |
| 8000 | 0.057000 | 0.132850 | 0.249126 |
| 8200 | 0.056100 | 0.128827 | 0.248252 |
| 8400 | 0.056400 | 0.130229 | 0.246795 |
| 8600 | 0.052800 | 0.128939 | 0.245775 |
| 8800 | 0.051100 | 0.131892 | 0.248543 |
| 9000 | 0.052900 | 0.132062 | 0.244464 |
| 9200 | 0.048200 | 0.130988 | 0.244172 |
| 9400 | 0.047700 | 0.131811 | 0.242570 |
| 9600 | 0.050000 | 0.133832 | 0.245484 |
| 9800 | 0.047500 | 0.134340 | 0.243881 |
| 10000 | 0.048400 | 0.133388 | 0.243590 |
| 10200 | 0.047800 | 0.132729 | 0.244464 |
| 10400 | 0.049000 | 0.131695 | 0.245047 |
| 10600 | 0.044400 | 0.132154 | 0.245484 |
| 10800 | 0.050100 | 0.131575 | 0.245192 |
| 11000 | 0.047700 | 0.131211 | 0.245192 |
| 11200 | 0.046000 | 0.131293 | 0.245047 |
### 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-lithuanian --dataset mozilla-foundation/common_voice_8_0 --config lt --split test
``` |