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--- |
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library_name: transformers |
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language: |
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- ja |
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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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- mozilla-foundation/common_voice_13_0 |
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- generated_from_trainer |
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datasets: |
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- common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Hubert-common_voice-ja-demo-phonemes-cosine-3e-5 |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - JA |
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type: common_voice_13_0 |
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config: ja |
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split: test |
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args: 'Config: ja, Training split: train+validation, Eval split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 1.0 |
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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-common_voice-ja-demo-phonemes-cosine-3e-5 |
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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 MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - JA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: inf |
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- Wer: 1.0 |
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- Cer: 0.2359 |
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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: 16 |
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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: 32 |
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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: 20.0 |
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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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| No log | 0.2660 | 100 | inf | 1.8204 | 4.9067 | |
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| No log | 0.5319 | 200 | inf | 1.5926 | 4.6323 | |
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| No log | 0.7979 | 300 | inf | 1.1770 | 1.9637 | |
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| No log | 1.0638 | 400 | inf | 1.0 | 0.9817 | |
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| 14.493 | 1.3298 | 500 | inf | 1.0 | 0.9817 | |
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| 14.493 | 1.5957 | 600 | inf | 1.0 | 0.9817 | |
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| 14.493 | 1.8617 | 700 | inf | 1.0 | 0.9817 | |
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| 14.493 | 2.1277 | 800 | inf | 1.0 | 0.9817 | |
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| 14.493 | 2.3936 | 900 | inf | 1.0 | 0.9817 | |
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| 6.5744 | 2.6596 | 1000 | 6.8080 | 1.0 | 0.9817 | |
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| 6.5744 | 2.9255 | 1100 | 6.5972 | 1.0 | 0.9817 | |
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| 6.5744 | 3.1915 | 1200 | inf | 1.0 | 0.9817 | |
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| 6.5744 | 3.4574 | 1300 | inf | 1.0 | 0.9817 | |
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| 6.5744 | 3.7234 | 1400 | inf | 1.0 | 0.9817 | |
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| 5.5193 | 3.9894 | 1500 | inf | 1.0 | 0.9817 | |
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| 5.5193 | 4.2553 | 1600 | inf | 1.0 | 0.9817 | |
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| 5.5193 | 4.5213 | 1700 | inf | 1.0 | 0.9817 | |
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| 5.5193 | 4.7872 | 1800 | inf | 1.0 | 0.9817 | |
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| 5.5193 | 5.0532 | 1900 | inf | 1.0 | 0.9817 | |
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| 4.5578 | 5.3191 | 2000 | inf | 1.0 | 0.9817 | |
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| 4.5578 | 5.5851 | 2100 | inf | 1.0 | 0.9817 | |
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| 4.5578 | 5.8511 | 2200 | inf | 1.0 | 0.9817 | |
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| 4.5578 | 6.1170 | 2300 | inf | 1.0 | 0.9817 | |
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| 4.5578 | 6.3830 | 2400 | inf | 1.0 | 0.9817 | |
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| 3.6943 | 6.6489 | 2500 | inf | 1.0 | 0.9817 | |
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| 3.6943 | 6.9149 | 2600 | inf | 1.0 | 0.9817 | |
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| 3.6943 | 7.1809 | 2700 | inf | 1.0 | 0.9817 | |
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| 3.6943 | 7.4468 | 2800 | inf | 1.0 | 0.9817 | |
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| 3.6943 | 7.7128 | 2900 | 3.1572 | 1.0 | 0.9817 | |
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| 3.1932 | 7.9787 | 3000 | inf | 1.0 | 0.9817 | |
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| 3.1932 | 8.2447 | 3100 | inf | 1.0 | 0.9817 | |
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| 3.1932 | 8.5106 | 3200 | inf | 1.0 | 0.9817 | |
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| 3.1932 | 8.7766 | 3300 | inf | 1.0 | 0.9817 | |
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| 3.1932 | 9.0426 | 3400 | inf | 1.0 | 0.9817 | |
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| 3.0309 | 9.3085 | 3500 | inf | 1.0 | 0.9817 | |
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| 3.0309 | 9.5745 | 3600 | inf | 1.0 | 0.9817 | |
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| 3.0309 | 9.8404 | 3700 | inf | 1.0 | 0.9817 | |
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| 3.0309 | 10.1064 | 3800 | inf | 1.0 | 0.9817 | |
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| 3.0309 | 10.3723 | 3900 | inf | 1.0 | 0.9817 | |
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| 2.9704 | 10.6383 | 4000 | inf | 1.0 | 0.9817 | |
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| 2.9704 | 10.9043 | 4100 | inf | 1.0 | 0.9817 | |
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| 2.9704 | 11.1702 | 4200 | inf | 1.0 | 0.9049 | |
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| 2.9704 | 11.4362 | 4300 | inf | 1.0 | 0.7254 | |
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| 2.9704 | 11.7021 | 4400 | inf | 1.0 | 0.4365 | |
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| 2.2767 | 11.9681 | 4500 | 1.5675 | 1.0 | 0.3732 | |
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| 2.2767 | 12.2340 | 4600 | inf | 1.0 | 0.3455 | |
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| 2.2767 | 12.5 | 4700 | inf | 1.0 | 0.3277 | |
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| 2.2767 | 12.7660 | 4800 | inf | 1.0 | 0.3053 | |
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| 2.2767 | 13.0319 | 4900 | inf | 1.0 | 0.2935 | |
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| 1.2873 | 13.2979 | 5000 | inf | 1.0 | 0.2784 | |
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| 1.2873 | 13.5638 | 5100 | inf | 1.0 | 0.2684 | |
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| 1.2873 | 13.8298 | 5200 | inf | 1.0 | 0.2678 | |
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| 1.2873 | 14.0957 | 5300 | inf | 1.0 | 0.2616 | |
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| 1.2873 | 14.3617 | 5400 | 0.8214 | 1.0 | 0.2608 | |
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| 0.9318 | 14.6277 | 5500 | inf | 1.0 | 0.2564 | |
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| 0.9318 | 14.8936 | 5600 | inf | 1.0 | 0.2544 | |
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| 0.9318 | 15.1596 | 5700 | inf | 1.0 | 0.2525 | |
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| 0.9318 | 15.4255 | 5800 | inf | 1.0 | 0.2510 | |
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| 0.9318 | 15.6915 | 5900 | inf | 1.0 | 0.2527 | |
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| 0.754 | 15.9574 | 6000 | inf | 1.0 | 0.2499 | |
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| 0.754 | 16.2234 | 6100 | 0.6672 | 1.0 | 0.2485 | |
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| 0.754 | 16.4894 | 6200 | inf | 1.0 | 0.2464 | |
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| 0.754 | 16.7553 | 6300 | inf | 1.0 | 0.2467 | |
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| 0.754 | 17.0213 | 6400 | inf | 1.0 | 0.2411 | |
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| 0.6421 | 17.2872 | 6500 | inf | 1.0 | 0.2411 | |
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| 0.6421 | 17.5532 | 6600 | inf | 1.0 | 0.2418 | |
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| 0.6421 | 17.8191 | 6700 | inf | 1.0 | 0.2386 | |
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| 0.6421 | 18.0851 | 6800 | inf | 0.9996 | 0.2387 | |
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| 0.6421 | 18.3511 | 6900 | inf | 1.0 | 0.2381 | |
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| 0.568 | 18.6170 | 7000 | inf | 1.0 | 0.2391 | |
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| 0.568 | 18.8830 | 7100 | inf | 1.0 | 0.2370 | |
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| 0.568 | 19.1489 | 7200 | inf | 1.0 | 0.2344 | |
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| 0.568 | 19.4149 | 7300 | inf | 1.0 | 0.2364 | |
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| 0.568 | 19.6809 | 7400 | inf | 1.0 | 0.2347 | |
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| 0.5259 | 19.9468 | 7500 | inf | 1.0 | 0.2334 | |
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### Framework versions |
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- Transformers 4.47.0.dev0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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