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--- |
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language: |
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- hi |
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license: apache-2.0 |
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tags: |
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- Openslr Multilingual |
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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: Wav2Vec2_xls_r_300m_hi_final |
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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 7.0 |
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type: mozilla-foundation/common_voice_7_0 |
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args: hi |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 34.21 |
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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_xls_r_300m_hi_final |
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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 ['Openslr Multilingual and code-switching ASR challenge'](http://www.openslr.org/103/) dataset and ['mozilla-foundation/common_voice_7_0'](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3035 |
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- Wer: 0.3137 |
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- Cer: 0.0972 |
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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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 100 |
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- num_epochs: 8 |
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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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| 0.9821 | 0.64 | 400 | 0.5059 | 0.4783 | 0.1573 | |
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| 0.6861 | 1.28 | 800 | 0.4201 | 0.4247 | 0.1356 | |
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| 0.585 | 1.92 | 1200 | 0.3797 | 0.3811 | 0.1210 | |
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| 0.5193 | 2.56 | 1600 | 0.3577 | 0.3652 | 0.1152 | |
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| 0.4583 | 3.21 | 2000 | 0.3422 | 0.3519 | 0.1111 | |
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| 0.4282 | 3.85 | 2400 | 0.3261 | 0.3450 | 0.1071 | |
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| 0.3951 | 4.49 | 2800 | 0.3201 | 0.3325 | 0.1048 | |
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| 0.3619 | 5.13 | 3200 | 0.3167 | 0.3296 | 0.1030 | |
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| 0.345 | 5.77 | 3600 | 0.3157 | 0.3210 | 0.1013 | |
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| 0.338 | 6.41 | 4000 | 0.3051 | 0.3143 | 0.0982 | |
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| 0.3155 | 7.05 | 4400 | 0.3059 | 0.3154 | 0.0986 | |
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| 0.3057 | 7.69 | 4800 | 0.3035 | 0.3137 | 0.0972 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
