wav2vec2-large-xls-r-1B-common_voice-sl-ft
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.2112
- Wer: 0.1404
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.8291 | 12.2 | 500 | 0.5674 | 0.7611 |
0.0416 | 24.39 | 1000 | 0.3093 | 0.2964 |
0.0256 | 36.59 | 1500 | 0.2224 | 0.2072 |
0.0179 | 48.78 | 2000 | 0.2274 | 0.1960 |
0.0113 | 60.98 | 2500 | 0.2078 | 0.1582 |
0.0086 | 73.17 | 3000 | 0.1898 | 0.1552 |
0.0059 | 85.37 | 3500 | 0.2054 | 0.1446 |
0.0044 | 97.56 | 4000 | 0.2112 | 0.1404 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.10.3
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Dataset used to train reach-vb/wav2vec2-large-xls-r-1B-common_voice-sl-ft
Evaluation results
- Test WER on Common Voice 7self-reported23.260
- Test CER on Common Voice 7self-reported7.950
- Test WER on Common Voice 7.0self-reported13.590
- Test WER on Robust Speech Event - Dev Dataself-reported62.710
- Test WER on Robust Speech Event - Test Dataself-reported62.340