w2v-bert-2.0-japanese-CV16.0
This model is a fine-tuned version of Watarungurunnn/w2v-bert-2.0-japanese-CV16.0 on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.5149
- Wer: 32.6188
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1205 | 1.69 | 500 | 1.3602 | 36.4355 |
| 0.2116 | 3.39 | 1000 | 1.4580 | 35.1067 |
| 0.1054 | 5.08 | 1500 | 1.4180 | 34.6457 |
| 0.0661 | 6.78 | 2000 | 1.4557 | 32.3889 |
| 0.0208 | 8.47 | 2500 | 1.5149 | 32.6188 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Base model
Watarungurunnn/w2v-bert-2.0-japanese-CV16.0Evaluation results
- Wer on common_voice_16_0validation set self-reported32.619