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hubert-rinnna-jp-jdrtsp-fw07sp-13
This model is a fine-tuned version of rinna/japanese-hubert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1606
- Wer: 0.3004
- Cer: 0.1786
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: 0.0005
- train_batch_size: 32
- eval_batch_size: 16
- 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: 1000
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.352 | 1.0 | 404 | 0.9913 | 0.6021 | 0.4479 |
| 0.9044 | 2.0 | 808 | 0.5053 | 0.4261 | 0.2774 |
| 0.9001 | 3.0 | 1212 | 0.8458 | 0.4848 | 0.3267 |
| 0.8425 | 4.0 | 1616 | 0.5311 | 0.4577 | 0.3053 |
| 0.8408 | 5.0 | 2020 | 0.4328 | 0.4075 | 0.2776 |
| 0.7759 | 6.0 | 2424 | 0.4736 | 0.4394 | 0.3363 |
| 0.7228 | 7.0 | 2828 | 0.4667 | 0.4173 | 0.2862 |
| 0.6755 | 8.0 | 3232 | 0.4190 | 0.4114 | 0.2611 |
| 0.634 | 9.0 | 3636 | 0.4252 | 0.3993 | 0.2612 |
| 0.6267 | 10.0 | 4040 | 0.3275 | 0.3734 | 0.2362 |
| 0.6199 | 11.0 | 4444 | 0.2786 | 0.3543 | 0.2222 |
| 0.5396 | 12.0 | 4848 | 0.2851 | 0.3501 | 0.2146 |
| 0.5343 | 13.0 | 5252 | 0.2527 | 0.3448 | 0.2106 |
| 0.5488 | 14.0 | 5656 | 0.2725 | 0.3431 | 0.2100 |
| 0.4606 | 15.0 | 6060 | 0.2293 | 0.3259 | 0.1962 |
| 0.4229 | 16.0 | 6464 | 0.2043 | 0.3172 | 0.1914 |
| 0.4078 | 17.0 | 6868 | 0.1891 | 0.3128 | 0.1862 |
| 0.4017 | 18.0 | 7272 | 0.1785 | 0.3075 | 0.1833 |
| 0.3618 | 19.0 | 7676 | 0.1673 | 0.3035 | 0.1803 |
| 0.3739 | 20.0 | 8080 | 0.1606 | 0.3004 | 0.1786 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
