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--- |
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language: |
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- ar |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large Arabic |
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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: mozilla-foundation/common_voice_11_0 ar |
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type: mozilla-foundation/common_voice_11_0 |
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config: ar |
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split: test |
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args: ar |
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metrics: |
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- name: Wer |
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type: wer |
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value: 49.431999999999995 |
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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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# Whisper Large Arabic |
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This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the mozilla-foundation/common_voice_11_0 ar dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3231 |
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- Wer: 49.4320 |
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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: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 2 |
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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: 500 |
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- training_steps: 10000 |
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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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| 0.2472 | 0.1 | 1000 | 0.3719 | 58.9560 | |
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| 0.2015 | 0.2 | 2000 | 0.3487 | 53.5213 | |
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| 0.1418 | 1.04 | 3000 | 0.3231 | 49.4320 | |
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| 0.0921 | 1.14 | 4000 | 0.3284 | 56.1107 | |
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| 0.0923 | 1.24 | 5000 | 0.3304 | 61.4227 | |
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| 0.0483 | 2.08 | 6000 | 0.3460 | 55.952 | |
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| 0.0391 | 2.18 | 7000 | 0.3538 | 51.1067 | |
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| 0.0228 | 3.02 | 8000 | 0.3493 | 51.82 | |
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| 0.0206 | 3.12 | 9000 | 0.3729 | 52.4000 | |
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| 0.018 | 3.22 | 10000 | 0.3676 | 51.296 | |
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### Framework versions |
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- Transformers 4.28.0.dev0 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.11.1.dev0 |
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- Tokenizers 0.13.2 |
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