AndrewMcDowell
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Update README.md
Browse filesAdd eval results on dev data.
README.md
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- name: Test CER
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type: cer
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value: 23.64
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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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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - JA dataset.
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Kanji are converted into Hiragana using the [pykakasi](https://pykakasi.readthedocs.io/en/latest/index.html) library during training and evaluation. The model can output both Hiragana and Katakana characters.
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It achieves the following results on the evaluation set:
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- Loss: 0.5212
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```bash
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python ./eval.py --model_id AndrewMcDowell/wav2vec2-xls-r-300m-japanese --dataset mozilla-foundation/common_voice_8_0 --config ja --split test --log_outputs
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```
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- name: Test CER
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type: cer
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value: 23.64
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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: Robust Speech Event - Dev Data
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type: speech-recognition-community-v2/dev_data
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args: de
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metrics:
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- name: Test WER
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type: wer
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value: 1.0
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- name: Test CER
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type: cer
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value: 30.99
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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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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - JA dataset.
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Kanji are converted into Hiragana using the [pykakasi](https://pykakasi.readthedocs.io/en/latest/index.html) library during training and evaluation. The model can output both Hiragana and Katakana characters. Since there is no spacing, WER is not a suitable metric for evaluating performance and CER is more suitable.
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On mozilla-foundation/common_voice_8_0 it achieved:
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- cer: 23.64%
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On speech-recognition-community-v2/dev_data it achieved:
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- cer: 30.99%
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It achieves the following results on the evaluation set:
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- Loss: 0.5212
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```bash
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python ./eval.py --model_id AndrewMcDowell/wav2vec2-xls-r-300m-japanese --dataset mozilla-foundation/common_voice_8_0 --config ja --split test --log_outputs
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```
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2. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test`
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```bash
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python ./eval.py --model_id AndrewMcDowell/wav2vec2-xls-r-300m-japanese --dataset speech-recognition-community-v2/dev_data --config de --split validation --chunk_length_s 5.0 --stride_length_s 1.0
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```
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