wav2vec2-large-xls-r-300m-mongolian
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - MN dataset. It achieves the following results on the evaluation set:
- Loss: 0.6003
- Wer: 0.4473
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: 0.0003
- train_batch_size: 32
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 100.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.3677 | 15.87 | 2000 | 0.6432 | 0.6198 |
| 1.1379 | 31.75 | 4000 | 0.6196 | 0.5592 |
| 1.0093 | 47.62 | 6000 | 0.5828 | 0.5117 |
| 0.8888 | 63.49 | 8000 | 0.5754 | 0.4822 |
| 0.7985 | 79.37 | 10000 | 0.5987 | 0.4690 |
| 0.697 | 95.24 | 12000 | 0.6014 | 0.4471 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
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Dataset used to train infinitejoy/wav2vec2-large-xls-r-300m-mongolian
Evaluation results
- Test WER on Common Voice 7self-reported44.709
- Test CER on Common Voice 7self-reported13.532
- Test WER on Robust Speech Event - Dev Dataself-reported76.643
- Test CER on Robust Speech Event - Dev Dataself-reported36.997
- Test WER on Robust Speech Event - Test Dataself-reported78.450