This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the /WORKSPACE/DATA/HY/NOIZY_STUDENT_4/ - NA dataset. It achieves the following results on the evaluation set:
- Loss: 0.1693
- Wer: 0.2373
- Cer: 0.0429
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 842
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
1.255 | 7.24 | 500 | 0.2978 | 0.4294 | 0.0758 |
1.0058 | 14.49 | 1000 | 0.1883 | 0.2838 | 0.0483 |
0.9371 | 21.73 | 1500 | 0.1813 | 0.2627 | 0.0457 |
0.8999 | 28.98 | 2000 | 0.1693 | 0.2373 | 0.0429 |
0.8814 | 36.23 | 2500 | 0.1760 | 0.2420 | 0.0435 |
0.8364 | 43.47 | 3000 | 0.1765 | 0.2416 | 0.0419 |
0.8019 | 50.72 | 3500 | 0.1758 | 0.2311 | 0.0398 |
0.7665 | 57.96 | 4000 | 0.1745 | 0.2240 | 0.0399 |
0.7376 | 65.22 | 4500 | 0.1717 | 0.2190 | 0.0385 |
0.716 | 72.46 | 5000 | 0.1700 | 0.2147 | 0.0382 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2
- Datasets 1.18.4.dev0
- Tokenizers 0.11.0
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Dataset used to train arampacha/wav2vec2-xls-r-1b-hy
Evaluation results
- WER LM on Common Voice hy-AMself-reported10.812
- CER LM on Common Voice hy-AMself-reported2.221
- Test WER on Robust Speech Event - Dev Dataself-reported18.219
- Test CER on Robust Speech Event - Dev Dataself-reported7.076