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--- |
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language: |
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- ba |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- mozilla-foundation/common_voice_7_0 |
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- robust-speech-event |
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datasets: |
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- mozilla-foundation/common_voice_7_0 |
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model-index: |
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- name: XLS-R-300M - Bashkir |
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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 7 |
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type: mozilla-foundation/common_voice_7_0 |
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args: ba |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 24.2 |
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- name: Test CER |
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type: cer |
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value: 5.08 |
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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-xls-r-300m-bashkir |
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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_7_0 - BA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1892 |
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- Wer: 0.2421 |
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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: 32 |
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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: 2000 |
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- num_epochs: 10.0 |
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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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| 1.4792 | 0.5 | 2000 | 0.4598 | 0.5404 | |
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| 1.449 | 1.0 | 4000 | 0.4650 | 0.5610 | |
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| 1.3742 | 1.49 | 6000 | 0.4001 | 0.4977 | |
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| 1.3375 | 1.99 | 8000 | 0.3916 | 0.4894 | |
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| 1.2961 | 2.49 | 10000 | 0.3641 | 0.4569 | |
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| 1.2714 | 2.99 | 12000 | 0.3491 | 0.4488 | |
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| 1.2399 | 3.48 | 14000 | 0.3151 | 0.3986 | |
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| 1.2067 | 3.98 | 16000 | 0.3081 | 0.3923 | |
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| 1.1842 | 4.48 | 18000 | 0.2875 | 0.3703 | |
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| 1.1644 | 4.98 | 20000 | 0.2840 | 0.3670 | |
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| 1.161 | 5.48 | 22000 | 0.2790 | 0.3597 | |
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| 1.1303 | 5.97 | 24000 | 0.2552 | 0.3272 | |
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| 1.0874 | 6.47 | 26000 | 0.2405 | 0.3142 | |
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| 1.0613 | 6.97 | 28000 | 0.2352 | 0.3055 | |
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| 1.0498 | 7.47 | 30000 | 0.2249 | 0.2910 | |
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| 1.021 | 7.96 | 32000 | 0.2118 | 0.2752 | |
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| 1.0002 | 8.46 | 34000 | 0.2046 | 0.2662 | |
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| 0.9762 | 8.96 | 36000 | 0.1969 | 0.2530 | |
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| 0.9568 | 9.46 | 38000 | 0.1917 | 0.2449 | |
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| 0.953 | 9.96 | 40000 | 0.1893 | 0.2425 | |
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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 1.17.1.dev0 |
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- Tokenizers 0.11.0 |
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