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--- |
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language: |
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- de |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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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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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xlsr-53-german-cv13-restart |
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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: MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - DE |
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type: common_voice_13_0 |
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config: de |
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split: test |
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args: 'Config: de, Training split: train+validation, Eval split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.10748248671697858 |
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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-large-xlsr-53-german-cv13-restart |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co./facebook/wav2vec2-large-xlsr-53) on the MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - DE dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1121 |
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- Wer: 0.1075 |
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- Cer: 0.0286 |
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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: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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_ratio: 0.01 |
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- num_epochs: 15.0 |
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### Training results |
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| Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
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|:-------------:|:-----:|:-----:|:------:|:---------------:|:------:| |
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| 0.1679 | 1.0 | 4348 | 0.0459 | 0.1617 | 0.1707 | |
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| 0.1597 | 2.0 | 8697 | 0.0479 | 0.1592 | 0.1717 | |
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| 0.1364 | 3.0 | 13045 | 0.0425 | 0.1524 | 0.1563 | |
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| 0.1311 | 4.0 | 17394 | 0.0406 | 0.1446 | 0.1515 | |
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| 0.1152 | 5.0 | 21742 | 0.0397 | 0.1431 | 0.1470 | |
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| 0.107 | 6.0 | 26091 | 0.0369 | 0.1382 | 0.1377 | |
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| 0.0957 | 7.0 | 30439 | 0.0373 | 0.1343 | 0.1372 | |
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| 0.0924 | 8.0 | 34788 | 0.0355 | 0.1335 | 0.1315 | |
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| 0.0835 | 9.0 | 39136 | 0.0384 | 0.1328 | 0.1380 | |
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| 0.0775 | 10.0 | 43485 | 0.0328 | 0.1232 | 0.1229 | |
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| 0.0752 | 11.0 | 47833 | 0.0309 | 0.1220 | 0.1174 | |
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| 0.0691 | 12.0 | 52182 | 0.0327 | 0.1182 | 0.1197 | |
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| 0.0689 | 13.0 | 56530 | 0.0307 | 0.1163 | 0.1150 | |
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| 0.0653 | 14.0 | 60879 | 0.0304 | 0.1141 | 0.1126 | |
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| 0.0717 | 15.0 | 65220 | 0.1121 | 0.1075 | 0.0286 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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