wav2vec2-large-xls-r-300m-sat-a3
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SAT dataset. It achieves the following results on the evaluation set:
- Loss: 0.8961
- Wer: 0.3976
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-sat-a3 --dataset mozilla-foundation/common_voice_8_0 --config sat --split test --log_outputs
- To evaluate on speech-recognition-community-v2/dev_data
Note: Santali (Ol Chiki) language not found in speech-recognition-community-v2/dev_data
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0004
- 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: 200
- num_epochs: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 11.1266 | 33.29 | 100 | 2.8577 | 1.0 |
| 2.1549 | 66.57 | 200 | 1.0799 | 0.5542 |
| 0.5628 | 99.86 | 300 | 0.7973 | 0.4016 |
| 0.0779 | 133.29 | 400 | 0.8424 | 0.4177 |
| 0.0404 | 166.57 | 500 | 0.9048 | 0.4137 |
| 0.0212 | 199.86 | 600 | 0.8961 | 0.3976 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
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Dataset used to train DrishtiSharma/wav2vec2-large-xls-r-300m-sat-a3
Evaluation results
- Test WER on Common Voice 8self-reported0.357
- Test CER on Common Voice 8self-reported0.142
- Test WER on Robust Speech Event - Dev Dataself-reportedNA
- Test CER on Robust Speech Event - Dev Dataself-reportedNA