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--- |
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language: |
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- id |
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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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datasets: |
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- common_voice |
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model-index: |
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- name: 'XLS-R-300M - Indonesia' |
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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: sv-SE |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 38.098 |
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- name: Test CER |
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type: cer |
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value: 14.261 |
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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 - ID dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3975 |
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- Wer: 0.2633 |
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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: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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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: 500 |
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- num_epochs: 30.0 |
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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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| No log | 0.78 | 100 | 4.5645 | 1.0 | |
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| No log | 1.55 | 200 | 2.9016 | 1.0 | |
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| No log | 2.33 | 300 | 2.2666 | 1.0982 | |
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| No log | 3.1 | 400 | 0.6079 | 0.6376 | |
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| 3.2188 | 3.88 | 500 | 0.4985 | 0.5008 | |
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| 3.2188 | 4.65 | 600 | 0.4477 | 0.4469 | |
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| 3.2188 | 5.43 | 700 | 0.3953 | 0.3915 | |
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| 3.2188 | 6.2 | 800 | 0.4319 | 0.3921 | |
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| 3.2188 | 6.98 | 900 | 0.4171 | 0.3698 | |
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| 0.2193 | 7.75 | 1000 | 0.3957 | 0.3600 | |
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| 0.2193 | 8.53 | 1100 | 0.3730 | 0.3493 | |
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| 0.2193 | 9.3 | 1200 | 0.3780 | 0.3348 | |
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| 0.2193 | 10.08 | 1300 | 0.4133 | 0.3568 | |
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| 0.2193 | 10.85 | 1400 | 0.3984 | 0.3193 | |
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| 0.1129 | 11.63 | 1500 | 0.3845 | 0.3174 | |
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| 0.1129 | 12.4 | 1600 | 0.3882 | 0.3162 | |
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| 0.1129 | 13.18 | 1700 | 0.3982 | 0.3008 | |
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| 0.1129 | 13.95 | 1800 | 0.3902 | 0.3198 | |
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| 0.1129 | 14.73 | 1900 | 0.4082 | 0.3237 | |
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| 0.0765 | 15.5 | 2000 | 0.3732 | 0.3126 | |
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| 0.0765 | 16.28 | 2100 | 0.3893 | 0.3001 | |
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| 0.0765 | 17.05 | 2200 | 0.4168 | 0.3083 | |
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| 0.0765 | 17.83 | 2300 | 0.4193 | 0.3044 | |
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| 0.0765 | 18.6 | 2400 | 0.4006 | 0.3013 | |
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| 0.0588 | 19.38 | 2500 | 0.3836 | 0.2892 | |
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| 0.0588 | 20.16 | 2600 | 0.3761 | 0.2903 | |
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| 0.0588 | 20.93 | 2700 | 0.3895 | 0.2930 | |
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| 0.0588 | 21.71 | 2800 | 0.3885 | 0.2791 | |
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| 0.0588 | 22.48 | 2900 | 0.3902 | 0.2891 | |
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| 0.0448 | 23.26 | 3000 | 0.4200 | 0.2849 | |
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| 0.0448 | 24.03 | 3100 | 0.4013 | 0.2799 | |
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| 0.0448 | 24.81 | 3200 | 0.4039 | 0.2731 | |
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| 0.0448 | 25.58 | 3300 | 0.3970 | 0.2647 | |
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| 0.0448 | 26.36 | 3400 | 0.4081 | 0.2690 | |
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| 0.0351 | 27.13 | 3500 | 0.4090 | 0.2674 | |
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| 0.0351 | 27.91 | 3600 | 0.3953 | 0.2663 | |
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| 0.0351 | 28.68 | 3700 | 0.4044 | 0.2650 | |
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| 0.0351 | 29.46 | 3800 | 0.3969 | 0.2646 | |
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### Framework versions |
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- Transformers 4.17.0.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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