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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: rinna/japanese-hubert-base |
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tags: |
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- automatic-speech-recognition |
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- original_kakeiken_W_closed_add_ver2 |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: Hubert-kakeiken-W-closed_add_ver2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Hubert-kakeiken-W-closed_add_ver2 |
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This model is a fine-tuned version of [rinna/japanese-hubert-base](https://huggingface.co/rinna/japanese-hubert-base) on the ORIGINAL_KAKEIKEN_W_CLOSED_ADD_VER2 - JA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0617 |
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- Wer: 0.9988 |
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- Cer: 1.0129 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 12500 |
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- num_epochs: 40.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:| |
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| 28.4059 | 1.0 | 880 | 10.6721 | 1.0 | 1.1284 | |
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| 9.1792 | 2.0 | 1760 | 6.9924 | 1.0 | 1.1284 | |
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| 4.9143 | 3.0 | 2640 | 3.8166 | 1.0 | 1.1284 | |
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| 3.1394 | 4.0 | 3520 | 2.8829 | 1.0 | 1.1283 | |
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| 2.7266 | 5.0 | 4400 | 1.9608 | 1.0 | 1.1444 | |
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| 1.4314 | 6.0 | 5280 | 0.8434 | 0.9999 | 1.0662 | |
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| 0.6837 | 7.0 | 6160 | 0.4583 | 0.9997 | 1.0330 | |
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| 0.403 | 8.0 | 7040 | 0.2512 | 0.9991 | 1.0479 | |
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| 0.3035 | 9.0 | 7920 | 0.1972 | 0.9993 | 1.0365 | |
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| 0.229 | 10.0 | 8800 | 0.0872 | 0.9991 | 1.0264 | |
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| 0.1995 | 11.0 | 9680 | 0.0959 | 0.9988 | 1.0262 | |
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| 0.1824 | 12.0 | 10560 | 0.1012 | 0.9988 | 1.0317 | |
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| 0.1774 | 13.0 | 11440 | 0.0541 | 0.9991 | 1.0220 | |
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| 0.1739 | 14.0 | 12320 | 0.0703 | 0.9990 | 1.0270 | |
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| 0.1609 | 15.0 | 13200 | 0.0480 | 0.9988 | 1.0203 | |
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| 0.1512 | 16.0 | 14080 | 0.0540 | 0.9988 | 1.0162 | |
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| 0.1412 | 17.0 | 14960 | 0.0396 | 0.9988 | 1.0188 | |
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| 0.1391 | 18.0 | 15840 | 0.0493 | 0.9988 | 1.0195 | |
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| 0.1325 | 19.0 | 16720 | 0.0366 | 0.9988 | 1.0186 | |
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| 0.1242 | 20.0 | 17600 | 0.0392 | 0.9988 | 1.0178 | |
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| 0.122 | 21.0 | 18480 | 0.0545 | 0.9988 | 1.0193 | |
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| 0.1143 | 22.0 | 19360 | 0.0408 | 0.9988 | 1.0185 | |
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| 0.1087 | 23.0 | 20240 | 0.0310 | 0.9988 | 1.0176 | |
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| 0.1013 | 24.0 | 21120 | 0.0262 | 0.9988 | 1.0166 | |
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| 0.0998 | 25.0 | 22000 | 0.0388 | 0.9988 | 1.0199 | |
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| 0.0903 | 26.0 | 22880 | 0.0280 | 0.9988 | 1.0166 | |
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| 0.088 | 27.0 | 23760 | 0.0492 | 0.9988 | 1.0197 | |
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| 0.0838 | 28.0 | 24640 | 0.0230 | 0.9988 | 1.0163 | |
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| 0.079 | 29.0 | 25520 | 0.0282 | 0.9988 | 1.0170 | |
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| 0.0747 | 30.0 | 26400 | 0.0271 | 0.9988 | 1.0162 | |
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| 0.0692 | 31.0 | 27280 | 0.0272 | 0.9988 | 1.0167 | |
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| 0.0699 | 32.0 | 28160 | 0.0427 | 0.9988 | 1.0143 | |
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| 0.0652 | 33.0 | 29040 | 0.0324 | 0.9988 | 1.0162 | |
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| 0.0624 | 34.0 | 29920 | 0.0315 | 0.9988 | 1.0163 | |
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| 0.0588 | 35.0 | 30800 | 0.0549 | 0.9988 | 1.0137 | |
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| 0.0594 | 36.0 | 31680 | 0.0457 | 0.9988 | 1.0142 | |
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| 0.0619 | 37.0 | 32560 | 0.0463 | 0.9988 | 1.0144 | |
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| 0.058 | 38.0 | 33440 | 0.0665 | 0.9988 | 1.0127 | |
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| 0.059 | 39.0 | 34320 | 0.0595 | 0.9988 | 1.0131 | |
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| 0.0563 | 39.9551 | 35160 | 0.0581 | 0.9988 | 1.0133 | |
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### Framework versions |
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- Transformers 4.48.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.21.0 |
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