Akashpb13/Hausa_xlsr
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m It achieves the following results on the evaluation set (which is 10 percent of train data set merged with invalidated data, reported, other, and dev datasets):
- Loss: 0.275118
- Wer: 0.329955
Model description
"facebook/wav2vec2-xls-r-300m" was finetuned.
Intended uses & limitations
More information needed
Training and evaluation data
Training data - Common voice Hausa train.tsv, dev.tsv, invalidated.tsv, reported.tsv and other.tsv Only those points were considered where upvotes were greater than downvotes and duplicates were removed after concatenation of all the datasets given in common voice 7.0
Training procedure
For creating the training dataset, all possible datasets were appended and 90-10 split was used.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.000096
- train_batch_size: 16
- eval_batch_size: 16
- seed: 13
- gradient_accumulation_steps: 2
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 500
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
Step | Training Loss | Validation Loss | Wer |
---|---|---|---|
500 | 5.175900 | 2.750914 | 1.000000 |
1000 | 1.028700 | 0.338649 | 0.497999 |
1500 | 0.332200 | 0.246896 | 0.402241 |
2000 | 0.227300 | 0.239640 | 0.395839 |
2500 | 0.175000 | 0.239577 | 0.373966 |
3000 | 0.140400 | 0.243272 | 0.356095 |
3500 | 0.119200 | 0.263761 | 0.365164 |
4000 | 0.099300 | 0.265954 | 0.353428 |
4500 | 0.084400 | 0.276367 | 0.349693 |
5000 | 0.073700 | 0.282631 | 0.343825 |
5500 | 0.068000 | 0.282344 | 0.341158 |
6000 | 0.064500 | 0.281591 | 0.342491 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 1.18.3
- Tokenizers 0.10.3
Evaluation Commands
- To evaluate on
mozilla-foundation/common_voice_8_0
with splittest
python eval.py --model_id Akashpb13/Hausa_xlsr --dataset mozilla-foundation/common_voice_8_0 --config ha --split test
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Evaluation results
- Test WER on Common Voice 8self-reported0.206
- Test CER on Common Voice 8self-reported0.044
- Test WER on Robust Speech Event - Dev Dataself-reported0.206
- Test CER on Robust Speech Event - Dev Dataself-reported0.044