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--- |
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language: |
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- ka |
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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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- 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: wav2vec2-xls-r-1b-ka |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Speech Recognition |
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dataset: |
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type: mozilla-foundation/common_voice_8_0 |
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name: Common Voice ka |
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args: ka |
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metrics: |
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- type: wer |
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value: 7.39778066580026 |
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name: WER LM |
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- type: cer |
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value: 1.1882089427096434 |
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name: CER LM |
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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: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: ka |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 22.61 |
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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: Robust Speech Event - Test Data |
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type: speech-recognition-community-v2/eval_data |
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args: ka |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 21.58 |
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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-1b-ka |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the /WORKSPACE/DATA/KA/NOIZY_STUDENT_2/ - KA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1022 |
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- Wer: 0.1527 |
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- Cer: 0.0221 |
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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: 7e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- training_steps: 4000 |
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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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| 1.2839 | 6.45 | 400 | 0.2229 | 0.3609 | 0.0557 | |
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| 0.9775 | 12.9 | 800 | 0.1271 | 0.2202 | 0.0317 | |
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| 0.9045 | 19.35 | 1200 | 0.1268 | 0.2030 | 0.0294 | |
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| 0.8652 | 25.8 | 1600 | 0.1211 | 0.1940 | 0.0287 | |
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| 0.8505 | 32.26 | 2000 | 0.1192 | 0.1912 | 0.0276 | |
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| 0.8168 | 38.7 | 2400 | 0.1086 | 0.1763 | 0.0260 | |
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| 0.7737 | 45.16 | 2800 | 0.1098 | 0.1753 | 0.0256 | |
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| 0.744 | 51.61 | 3200 | 0.1054 | 0.1646 | 0.0239 | |
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| 0.7114 | 58.06 | 3600 | 0.1034 | 0.1573 | 0.0228 | |
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| 0.6773 | 64.51 | 4000 | 0.1022 | 0.1527 | 0.0221 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2 |
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- Datasets 1.18.4.dev0 |
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- Tokenizers 0.11.0 |
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