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--- |
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language: |
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- hsb |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_8_0 |
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- generated_from_trainer |
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- robust-speech-event |
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- xlsr-fine-tuning-week |
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- hf-asr-leaderboard |
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datasets: |
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- common_voice |
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model-index: |
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- name: Upper Sorbian comodoro Wav2Vec2 XLSR 300M CV8 |
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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: Common Voice 8 |
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type: mozilla-foundation/common_voice_8_0 |
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args: hsb |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 56.3 |
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- name: Test CER |
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type: cer |
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value: 14.3 |
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--- |
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# Upper Sorbian wav2vec2-xls-r-300m-hsb-cv8 |
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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 common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9643 |
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- Wer: 0.5037 |
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- Cer: 0.1278 |
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## Evaluation |
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The model can be evaluated using the attached `eval.py` script: |
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``` |
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python eval.py --model_id comodoro/wav2vec2-xls-r-300m-hsb-cv8 --dataset mozilla-foundation/common-voice_8_0 --split test --config hsb |
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``` |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 200 |
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- num_epochs: 500 |
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- mixed_precision_training: Native AMP |
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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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| 4.3121 | 19.35 | 1200 | 3.2059 | 1.0 | 1.0 | |
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| 2.6525 | 38.71 | 2400 | 1.1324 | 0.9387 | 0.3204 | |
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| 1.3644 | 58.06 | 3600 | 0.8767 | 0.8099 | 0.2271 | |
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| 1.093 | 77.42 | 4800 | 0.8739 | 0.7603 | 0.2090 | |
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| 0.9546 | 96.77 | 6000 | 0.8454 | 0.6983 | 0.1882 | |
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| 0.8554 | 116.13 | 7200 | 0.8197 | 0.6484 | 0.1708 | |
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| 0.775 | 135.48 | 8400 | 0.8452 | 0.6345 | 0.1681 | |
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| 0.7167 | 154.84 | 9600 | 0.8551 | 0.6241 | 0.1631 | |
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| 0.6609 | 174.19 | 10800 | 0.8442 | 0.5821 | 0.1531 | |
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| 0.616 | 193.55 | 12000 | 0.8892 | 0.5864 | 0.1527 | |
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| 0.5815 | 212.9 | 13200 | 0.8839 | 0.5772 | 0.1503 | |
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| 0.55 | 232.26 | 14400 | 0.8905 | 0.5665 | 0.1436 | |
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| 0.5173 | 251.61 | 15600 | 0.8995 | 0.5471 | 0.1417 | |
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| 0.4969 | 270.97 | 16800 | 0.8633 | 0.5325 | 0.1334 | |
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| 0.4803 | 290.32 | 18000 | 0.9074 | 0.5253 | 0.1352 | |
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| 0.4596 | 309.68 | 19200 | 0.9159 | 0.5146 | 0.1294 | |
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| 0.4415 | 329.03 | 20400 | 0.9055 | 0.5189 | 0.1314 | |
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| 0.434 | 348.39 | 21600 | 0.9435 | 0.5208 | 0.1314 | |
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| 0.4199 | 367.74 | 22800 | 0.9199 | 0.5136 | 0.1290 | |
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| 0.4008 | 387.1 | 24000 | 0.9342 | 0.5174 | 0.1303 | |
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| 0.4051 | 406.45 | 25200 | 0.9436 | 0.5132 | 0.1292 | |
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| 0.3861 | 425.81 | 26400 | 0.9417 | 0.5084 | 0.1283 | |
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| 0.3738 | 445.16 | 27600 | 0.9573 | 0.5079 | 0.1299 | |
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| 0.3768 | 464.52 | 28800 | 0.9682 | 0.5062 | 0.1289 | |
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| 0.3647 | 483.87 | 30000 | 0.9643 | 0.5037 | 0.1278 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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