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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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model-index: |
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- name: rinna-Hubert-eval |
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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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# rinna-Hubert-eval |
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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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- eval_loss: 19.8934 |
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- eval_model_preparation_time: 0.0098 |
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- eval_wer: 1.4341 |
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- eval_cer: 5.0433 |
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- eval_runtime: 206.2601 |
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- eval_samples_per_second: 24.042 |
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- eval_steps_per_second: 3.006 |
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- step: 0 |
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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: 0.0003 |
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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: 1.0 |
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- mixed_precision_training: Native AMP |
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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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