đ sammy786/wav2vec2-xlsr-interlingua
This model is a fine - tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA - FOUNDATION/COMMON_VOICE_8_0 - ia dataset. It provides a solution for automatic speech recognition, leveraging the pre - trained capabilities of the base model and adapting them to the specific dataset.
⨠Features
- Fine - Tuned Model: Based on facebook/wav2vec2-xls-r-1b, fine - tuned on the MOZILLA - FOUNDATION/COMMON_VOICE_8_0 - ia dataset.
- Evaluation Results: Achieves specific loss, WER, and CER values on the evaluation set, demonstrating its performance in automatic speech recognition.
đĻ Installation
No installation steps are provided in the original document, so this section is skipped.
đģ Usage Examples
No code examples are provided in the original document, so this section is skipped.
đ Documentation
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: 30
- mixed_precision_training: Native AMP
Training results
| Step |
Training Loss |
Validation Loss |
Wer |
| 200 |
4.649200 |
0.483339 |
0.511322 |
| 400 |
0.764700 |
0.133428 |
0.251288 |
| 600 |
0.563700 |
0.099292 |
0.227745 |
| 800 |
0.438800 |
0.087545 |
0.217445 |
| 1000 |
0.406800 |
0.072313 |
0.213848 |
| 1200 |
0.237500 |
0.066965 |
0.213766 |
| 1400 |
0.177800 |
0.064419 |
0.208126 |
| 1600 |
0.157100 |
0.065962 |
0.214011 |
| 1800 |
0.146600 |
0.059477 |
0.202076 |
| 2000 |
0.132800 |
0.055015 |
0.201831 |
| 2200 |
0.122000 |
0.055421 |
0.201749 |
| 2400 |
0.115700 |
0.054462 |
0.197826 |
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_0 with split test
python eval.py --model_id sammy786/wav2vec2-xlsr-interlingua --dataset mozilla - foundation/common_voice_8_0 --config ia --split test
đ§ Technical Details
This model achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):
đ License
This model is released under the Apache - 2.0 license.
| Property |
Details |
| Model Type |
Fine - tuned version of facebook/wav2vec2-xls-r-1b for automatic speech recognition |
| Training Data |
Common voice Finnish train.tsv, dev.tsv and other.tsv |
| License |
Apache - 2.0 |
%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
