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wav2vec2-large-xls-r-300m-ja-colab-3
This model is a fine-tuned version of pinot/wav2vec2-large-xls-r-300m-ja-colab-2 on the common_voice_10_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.2696
- Wer: 0.2299
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
No log | 1.0 | 637 | 1.4666 | 0.2862 |
No log | 2.0 | 1274 | 1.4405 | 0.2866 |
No log | 3.0 | 1911 | 1.4162 | 0.2762 |
No log | 4.0 | 2548 | 1.4128 | 0.2709 |
0.2814 | 5.0 | 3185 | 1.3927 | 0.2613 |
0.2814 | 6.0 | 3822 | 1.3629 | 0.2536 |
0.2814 | 7.0 | 4459 | 1.3349 | 0.2429 |
0.2814 | 8.0 | 5096 | 1.3116 | 0.2356 |
0.1624 | 9.0 | 5733 | 1.2774 | 0.2307 |
0.1624 | 10.0 | 6370 | 1.2696 | 0.2299 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.10.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1