Create README.md
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README.md
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---
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language:
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- lt
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license: apache-2.0
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tags:
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- automatic-speech-recognition
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- mozilla-foundation/common_voice_8_0
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- generated_from_trainer
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- fi
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- robust-speech-event
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- model_for_talk
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datasets:
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- mozilla-foundation/common_voice_8_0
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model-index:
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- name: sammy786/wav2vec2-xlsr-lithuanian
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Common Voice 8
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type: mozilla-foundation/common_voice_8_0
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args: fi
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metrics:
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- name: Test WER
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type: wer
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value: 39.10
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- name: Test CER
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type: cer
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value: 11.38
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Robust Speech Event - Dev Data
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type: speech-recognition-community-v2/dev_data
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args: lt
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metrics:
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- name: Test WER
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type: wer
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value: 39.10
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- name: Test CER
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type: cer
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value: 11.38
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---
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# sammy786/wav2vec2-xlsr-lithuanian
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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.
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It achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):
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- Loss: 13.1811
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- Wer: 24.2570
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## Model description
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"facebook/wav2vec2-xls-r-1b" was finetuned.
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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Training data -
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Common voice Finnish train.tsv, dev.tsv and other.tsv
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## Training procedure
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For creating the train dataset, all possible datasets were appended and 90-10 split was used.
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.000045637994662983496
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- train_batch_size: 8
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- eval_batch_size: 16
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- seed: 13
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine_with_restarts
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 40
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- mixed_precision_training: Native AMP
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### Training results
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| Step | Training Loss | Validation Loss | Wer |
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|:-----:|:-------------:|:---------------:|:--------:|
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| 200 | 5.718700 | 2.897032 | 1.000000 |
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| 400 | 1.340000 | 0.309548 | 0.507284 |
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| 600 | 0.799100 | 0.220205 | 0.402098 |
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| 800 | 0.494400 | 0.185093 | 0.352855 |
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| 1000 | 0.370800 | 0.165869 | 0.334207 |
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| 1200 | 0.312500 | 0.159801 | 0.324009 |
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| 1400 | 0.276100 | 0.148066 | 0.321678 |
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| 1600 | 0.250100 | 0.153748 | 0.311626 |
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| 1800 | 0.226400 | 0.147437 | 0.302885 |
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| 2000 | 0.206900 | 0.141176 | 0.296037 |
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| 2200 | 0.189900 | 0.142161 | 0.288170 |
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| 2400 | 0.192100 | 0.138029 | 0.286568 |
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| 2600 | 0.175600 | 0.139496 | 0.283654 |
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| 2800 | 0.156900 | 0.138609 | 0.283217 |
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| 3000 | 0.149400 | 0.140468 | 0.281906 |
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| 3200 | 0.144600 | 0.132472 | 0.278263 |
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| 3400 | 0.144100 | 0.141028 | 0.277535 |
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| 3600 | 0.133000 | 0.134287 | 0.275495 |
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| 3800 | 0.126600 | 0.149136 | 0.277681 |
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| 4000 | 0.123500 | 0.132180 | 0.266463 |
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| 4200 | 0.113000 | 0.137942 | 0.268211 |
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| 4400 | 0.111700 | 0.140038 | 0.272873 |
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| 4600 | 0.108600 | 0.136756 | 0.264132 |
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| 4800 | 0.103600 | 0.137541 | 0.263403 |
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| 5000 | 0.098000 | 0.140435 | 0.264860 |
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| 5200 | 0.095800 | 0.136950 | 0.262383 |
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| 5400 | 0.094000 | 0.128214 | 0.263986 |
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| 5600 | 0.085300 | 0.125024 | 0.259761 |
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| 5800 | 0.078900 | 0.128575 | 0.260198 |
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| 6000 | 0.083300 | 0.135496 | 0.258887 |
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| 6200 | 0.078800 | 0.131706 | 0.259178 |
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| 6400 | 0.073800 | 0.128451 | 0.255390 |
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| 6600 | 0.072600 | 0.131245 | 0.252768 |
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| 6800 | 0.073300 | 0.131525 | 0.249417 |
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| 7000 | 0.069000 | 0.128627 | 0.255536 |
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| 7200 | 0.064400 | 0.127767 | 0.250583 |
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| 7400 | 0.065400 | 0.129557 | 0.247815 |
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| 7600 | 0.061200 | 0.129734 | 0.250146 |
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| 7800 | 0.059100 | 0.135124 | 0.249709 |
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| 8000 | 0.057000 | 0.132850 | 0.249126 |
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| 8200 | 0.056100 | 0.128827 | 0.248252 |
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| 8400 | 0.056400 | 0.130229 | 0.246795 |
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| 8600 | 0.052800 | 0.128939 | 0.245775 |
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| 8800 | 0.051100 | 0.131892 | 0.248543 |
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| 9000 | 0.052900 | 0.132062 | 0.244464 |
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| 9200 | 0.048200 | 0.130988 | 0.244172 |
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| 9400 | 0.047700 | 0.131811 | 0.242570 |
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| 9600 | 0.050000 | 0.133832 | 0.245484 |
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| 9800 | 0.047500 | 0.134340 | 0.243881 |
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| 10000 | 0.048400 | 0.133388 | 0.243590 |
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| 10200 | 0.047800 | 0.132729 | 0.244464 |
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| 10400 | 0.049000 | 0.131695 | 0.245047 |
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| 10600 | 0.044400 | 0.132154 | 0.245484 |
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| 10800 | 0.050100 | 0.131575 | 0.245192 |
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| 11000 | 0.047700 | 0.131211 | 0.245192 |
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| 11200 | 0.046000 | 0.131293 | 0.245047 |
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### Framework versions
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- Transformers 4.16.0.dev0
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- Pytorch 1.10.0+cu102
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- Datasets 1.17.1.dev0
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- Tokenizers 0.10.3
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#### Evaluation Commands
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1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test`
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```bash
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python eval.py --model_id sammy786/wav2vec2-xlsr-lithuanian --dataset mozilla-foundation/common_voice_8_0 --config lt --split test
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```
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