wav2vec2-large-xls-r-300m-vi-colab
This model is a fine-tuned version of daila/wav2vec2-large-xls-r-300m-vi-colab on the common_voice_16_1 dataset. It achieves the following results on the evaluation set:
- Loss: 1.6432
- Wer: 0.5895
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: 0.0003
- 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: 30
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0916 | 4.52 | 400 | 1.5440 | 0.6357 |
0.1344 | 9.04 | 800 | 1.6043 | 0.6543 |
0.0926 | 13.56 | 1200 | 1.7226 | 0.6365 |
0.0703 | 18.08 | 1600 | 1.5989 | 0.6048 |
0.0557 | 22.6 | 2000 | 1.6714 | 0.6001 |
0.051 | 27.12 | 2400 | 1.6432 | 0.5895 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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