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--- |
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language: |
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- ha |
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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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- mozilla-foundation/common_voice_8_0 |
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model-index: |
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- name: '' |
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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 8.0 |
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type: mozilla-foundation/common_voice_8_0 |
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args: ha |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 51.31 |
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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 - HA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4998 |
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- Wer: 0.5153 |
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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: 9.6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 80.0 |
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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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| 3.0021 | 8.33 | 500 | 2.9059 | 1.0 | |
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| 2.6604 | 16.66 | 1000 | 2.6402 | 0.9892 | |
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| 1.2216 | 24.99 | 1500 | 0.6051 | 0.6851 | |
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| 1.0754 | 33.33 | 2000 | 0.5408 | 0.6464 | |
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| 0.9582 | 41.66 | 2500 | 0.5521 | 0.5935 | |
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| 0.8653 | 49.99 | 3000 | 0.5156 | 0.5550 | |
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| 0.7867 | 58.33 | 3500 | 0.5439 | 0.5606 | |
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| 0.7265 | 66.66 | 4000 | 0.4863 | 0.5255 | |
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| 0.6699 | 74.99 | 4500 | 0.5050 | 0.5169 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu113 |
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- Datasets 1.18.4.dev0 |
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- Tokenizers 0.11.0 |
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