wav2vec2-large-xls-r-300m-vot-final-a2
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - VOT dataset. It achieves the following results on the evaluation set:
- Loss: 2.8745
- Wer: 0.8333
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-vot-final-a2 --dataset mozilla-foundation/common_voice_8_0 --config vot --split test --log_outputs
- To evaluate on speech-recognition-community-v2/dev_data
Votic language isn't available 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: 340
- num_epochs: 200
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
11.1216 | 33.33 | 100 | 4.2848 | 1.0 |
2.9982 | 66.67 | 200 | 2.8665 | 1.0 |
1.5476 | 100.0 | 300 | 2.3022 | 0.8889 |
0.2776 | 133.33 | 400 | 2.7480 | 0.8889 |
0.1136 | 166.67 | 500 | 2.5383 | 0.8889 |
0.0489 | 200.0 | 600 | 2.8745 | 0.8333 |
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-vot-final-a2
Evaluation results
- Test WER on Common Voice 8self-reported0.833
- Test CER on Common Voice 8self-reported0.487
- Test WER on Robust Speech Event - Dev Dataself-reportedNA
- Test CER on Robust Speech Event - Dev Dataself-reportedNA