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--- |
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license: apache-2.0 |
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base_model: jonatasgrosman/wav2vec2-large-xlsr-53-japanese |
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tags: |
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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: wav2vec2phone-large-xlsr-jp-jdrt5N-demo |
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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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# wav2vec2phone-large-xlsr-jp-jdrt5N-demo |
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This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-japanese](https://huggingface.co./jonatasgrosman/wav2vec2-large-xlsr-53-japanese) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3714 |
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- Wer: 0.4730 |
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- Cer: 0.5054 |
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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: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 15 |
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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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| 1.5238 | 1.0 | 567 | 1.3532 | 0.8709 | 0.6208 | |
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| 1.2812 | 2.0 | 1134 | 0.8674 | 0.6835 | 0.5633 | |
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| 1.1329 | 3.0 | 1701 | 0.7105 | 0.6164 | 0.5564 | |
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| 1.0267 | 4.0 | 2268 | 0.6111 | 0.5775 | 0.5401 | |
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| 1.0415 | 5.0 | 2835 | 0.5505 | 0.5499 | 0.5482 | |
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| 0.9767 | 6.0 | 3402 | 0.4986 | 0.5210 | 0.5204 | |
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| 1.0392 | 7.0 | 3969 | 0.4655 | 0.5082 | 0.5194 | |
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| 0.9235 | 8.0 | 4536 | 0.4457 | 0.4989 | 0.5136 | |
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| 0.9511 | 9.0 | 5103 | 0.4201 | 0.4917 | 0.5106 | |
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| 0.8998 | 10.0 | 5670 | 0.4031 | 0.4869 | 0.5081 | |
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| 0.8883 | 11.0 | 6237 | 0.3920 | 0.4814 | 0.5107 | |
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| 0.856 | 12.0 | 6804 | 0.3834 | 0.4790 | 0.5094 | |
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| 0.8814 | 13.0 | 7371 | 0.3772 | 0.4761 | 0.5081 | |
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| 0.8352 | 14.0 | 7938 | 0.3737 | 0.4735 | 0.5052 | |
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| 0.9001 | 15.0 | 8505 | 0.3714 | 0.4730 | 0.5054 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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