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wav2vec2-large-xls-r-300m-bas-v1
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - BAS dataset. It achieves the following results on the evaluation set:
- Loss: 0.5997
- Wer: 0.3870
Evaluation Commands
- To evaluate on mozilla-foundation/common_voice_8_0 with test split
python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-bas-v1 --dataset mozilla-foundation/common_voice_8_0 --config bas --split test --log_outputs
- To evaluate on speech-recognition-community-v2/dev_data
Basaa (bas) language isn't available in speech-recognition-community-v2/dev_data
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.000111
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 12.7076 | 5.26 | 200 | 3.6361 | 1.0 |
| 3.1657 | 10.52 | 400 | 3.0101 | 1.0 |
| 2.3987 | 15.78 | 600 | 0.9125 | 0.6774 |
| 1.0079 | 21.05 | 800 | 0.6477 | 0.5352 |
| 0.7392 | 26.31 | 1000 | 0.5432 | 0.4929 |
| 0.6114 | 31.57 | 1200 | 0.5498 | 0.4639 |
| 0.5222 | 36.83 | 1400 | 0.5220 | 0.4561 |
| 0.4648 | 42.1 | 1600 | 0.5586 | 0.4289 |
| 0.4103 | 47.36 | 1800 | 0.5337 | 0.4082 |
| 0.3692 | 52.62 | 2000 | 0.5421 | 0.3861 |
| 0.3403 | 57.88 | 2200 | 0.5549 | 0.4096 |
| 0.3011 | 63.16 | 2400 | 0.5833 | 0.3925 |
| 0.2932 | 68.42 | 2600 | 0.5674 | 0.3815 |
| 0.2696 | 73.68 | 2800 | 0.5734 | 0.3889 |
| 0.2496 | 78.94 | 3000 | 0.5968 | 0.3985 |
| 0.2289 | 84.21 | 3200 | 0.5888 | 0.3893 |
| 0.2091 | 89.47 | 3400 | 0.5849 | 0.3852 |
| 0.2005 | 94.73 | 3600 | 0.5938 | 0.3875 |
| 0.1876 | 99.99 | 3800 | 0.5997 | 0.3870 |
Framework versions
- Transformers 4.16.1
- Pytorch 1.10.0+cu111
- Datasets 1.18.2
- Tokenizers 0.11.0
