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wav2vec2-xlsr-sakha
sammy786/wav2vec2-xlsr-sakha
wav2vec2-xlsr-sakha is a automatic speech recognition model from sammy786. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMONVOICE80 - sah dataset. It achieves the following results on evaluation set (which is 10 percent of train data set merged…
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Mar 24, 2022
- SHA
- 06627f36
Model card
From the Hugging Face model README
sammy786/wav2vec2-xlsr-sakha
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - sah dataset. It achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):
- Loss: 21.39
- Wer: 30.99
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: 15
- mixed_precision_training: Native AMP
Training results
| Step | Training Loss | Validation Loss | Wer |
|---|---|---|---|
| 200 | 4.541600 | 1.044711 | 0.926395 |
| 400 | 1.013700 | 0.290368 | 0.401758 |
| 600 | 0.645000 | 0.232261 | 0.346555 |
| 800 | 0.467800 | 0.214120 | 0.318340 |
| 1000 | 0.502300 | 0.213995 | 0.309957 |
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-sakha --dataset mozilla-foundation/common_voice_8_0 --config sah --split test
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Languages
- sah
- Created
- Mar 2, 2022
- Updated
- Mar 24, 2022