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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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tags: |
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- generated_from_trainer |
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datasets: |
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- audiofolder |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-xls-r-300m-ja-phoneme_cv_14_4 |
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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: audiofolder |
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type: audiofolder |
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config: default |
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split: train[:50%] |
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args: default |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.08746348761547412 |
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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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# wav2vec2-xls-r-300m-ja-phoneme_cv_14_4 |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co./facebook/wav2vec2-xls-r-300m) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3806 |
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- Wer: 0.0875 |
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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: 0.0001 |
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- train_batch_size: 2 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 5.8739 | 0.1 | 400 | 2.8760 | 1.0 | |
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| 1.8658 | 0.2 | 800 | 0.7874 | 0.1632 | |
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| 0.7464 | 0.29 | 1200 | 0.5934 | 0.1300 | |
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| 0.6031 | 0.39 | 1600 | 0.5022 | 0.1131 | |
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| 0.5313 | 0.49 | 2000 | 0.4730 | 0.1053 | |
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| 0.4973 | 0.59 | 2400 | 0.4571 | 0.1012 | |
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| 0.4686 | 0.69 | 2800 | 0.4156 | 0.0962 | |
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| 0.4315 | 0.79 | 3200 | 0.3926 | 0.0916 | |
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| 0.4192 | 0.88 | 3600 | 0.3865 | 0.0886 | |
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| 0.4055 | 0.98 | 4000 | 0.3806 | 0.0875 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.3 |
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- Tokenizers 0.13.3 |
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