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--- |
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language: |
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- eu |
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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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- et |
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- hf-asr-leaderboard |
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datasets: |
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- mozilla-foundation/common_voice_8_0 |
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model-index: |
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- name: xls-r-eus |
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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: eu |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 0.17871523648578164 |
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- name: Test CER |
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type: cer |
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value: 0.032624506085144 |
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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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# |
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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 - EU dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2278 |
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- Wer: 0.1787 |
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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: 72 |
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- eval_batch_size: 72 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 144 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 100.0 |
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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 | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 0.2548 | 4.24 | 500 | 0.2470 | 0.3663 | |
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| 0.1435 | 8.47 | 1000 | 0.2000 | 0.2791 | |
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| 0.1158 | 12.71 | 1500 | 0.2030 | 0.2652 | |
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| 0.1094 | 16.95 | 2000 | 0.2096 | 0.2605 | |
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| 0.1004 | 21.19 | 2500 | 0.2150 | 0.2477 | |
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| 0.0945 | 25.42 | 3000 | 0.2072 | 0.2369 | |
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| 0.0844 | 29.66 | 3500 | 0.1981 | 0.2328 | |
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| 0.0877 | 33.89 | 4000 | 0.2041 | 0.2425 | |
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| 0.0741 | 38.14 | 4500 | 0.2353 | 0.2421 | |
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| 0.0676 | 42.37 | 5000 | 0.2092 | 0.2213 | |
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| 0.0623 | 46.61 | 5500 | 0.2217 | 0.2250 | |
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| 0.0574 | 50.84 | 6000 | 0.2152 | 0.2179 | |
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| 0.0583 | 55.08 | 6500 | 0.2207 | 0.2186 | |
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| 0.0488 | 59.32 | 7000 | 0.2225 | 0.2159 | |
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| 0.0456 | 63.56 | 7500 | 0.2293 | 0.2031 | |
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| 0.041 | 67.79 | 8000 | 0.2277 | 0.2013 | |
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| 0.0379 | 72.03 | 8500 | 0.2287 | 0.1991 | |
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| 0.0381 | 76.27 | 9000 | 0.2233 | 0.1954 | |
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| 0.0308 | 80.51 | 9500 | 0.2195 | 0.1835 | |
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| 0.0291 | 84.74 | 10000 | 0.2266 | 0.1825 | |
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| 0.0266 | 88.98 | 10500 | 0.2285 | 0.1801 | |
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| 0.0266 | 93.22 | 11000 | 0.2292 | 0.1801 | |
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| 0.0262 | 97.46 | 11500 | 0.2278 | 0.1788 | |
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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 1.18.4.dev0 |
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- Tokenizers 0.11.0 |
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