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update evaluation
Browse files- README.md +9 -5
- log_mozilla-foundation_common_voice_8_0_de_test_predictions.txt +0 -0
- log_mozilla-foundation_common_voice_8_0_de_test_predictions_greedy.txt +0 -0
- mozilla-foundation_common_voice_8_0_de_test_eval_results.txt +2 -2
- mozilla-foundation_common_voice_8_0_de_test_eval_results_greedy.txt +2 -2
README.md
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metrics:
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- name: Test WER
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type: wer
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value:
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- name: Test CER
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type: cer
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value:
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- name: Test WER (+LM)
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type: wer
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value:
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- name: Test CER (+LM)
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type: cer
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value:
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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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# XLS-R-1B-GERMAN
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## Evaluation Commands
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metrics:
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- name: Test WER
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type: wer
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value: 10.95
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- name: Test CER
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type: cer
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value: 2.72
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- name: Test WER (+LM)
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type: wer
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value: 8.13
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- name: Test CER (+LM)
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type: cer
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value: 2.18
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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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# XLS-R-1B-GERMAN
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Fine-tuned [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on German using the [Common Voice 8](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0).
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When using this model, make sure that your speech input is sampled at 16kHz.
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This model has been fine-tuned thanks to the GPU credits generously given by the [OVHcloud](https://www.ovhcloud.com/en/public-cloud/ai-training/) :)
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The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
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## Evaluation Commands
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log_mozilla-foundation_common_voice_8_0_de_test_predictions.txt
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log_mozilla-foundation_common_voice_8_0_de_test_predictions_greedy.txt
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mozilla-foundation_common_voice_8_0_de_test_eval_results.txt
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WER: 0.
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CER: 0.
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WER: 0.08132936859765662
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CER: 0.0218942169889596
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mozilla-foundation_common_voice_8_0_de_test_eval_results_greedy.txt
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WER: 0.
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CER: 0.
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WER: 0.10957129022137957
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CER: 0.027228823349596854
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