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This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - AB dataset. It achieves the following results on the evaluation set:
- Loss: 0.5620
- Wer: 0.5651
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-ab-CV7 --dataset mozilla-foundation/common_voice_7_0 --config ab --split test --log_outputs
- To evaluate on speech-recognition-community-v2/dev_data
NA
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 7.5e-05
- 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: 2000
- num_epochs: 100.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
9.6445 | 13.64 | 300 | 4.3963 | 1.0 |
3.6459 | 27.27 | 600 | 3.2267 | 1.0 |
3.0978 | 40.91 | 900 | 3.0927 | 1.0 |
2.8357 | 54.55 | 1200 | 2.1462 | 1.0029 |
1.2723 | 68.18 | 1500 | 0.6747 | 0.6996 |
0.6528 | 81.82 | 1800 | 0.5928 | 0.6422 |
0.4905 | 95.45 | 2100 | 0.5587 | 0.5681 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0