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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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- ar-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_1 |
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metrics: |
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- wer |
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base_model: openai/whisper-medium |
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model-index: |
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- name: Whisper Medium Ar - AxAI |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: Client |
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type: mozilla-foundation/common_voice_16_1 |
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config: default |
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split: None |
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args: default |
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metrics: |
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- type: wer |
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value: 100.0 |
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name: Wer |
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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 Medium Ar - AxAI |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Client dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.5466 |
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- Wer: 100.0 |
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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: 1 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 8 |
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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: 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 | |
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|:-------------:|:------:|:----:|:---------------:|:-----:| |
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| 0.0411 | 24.39 | 500 | 2.8748 | 100.0 | |
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| 0.0063 | 48.78 | 1000 | 3.3347 | 100.0 | |
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| 0.0017 | 73.17 | 1500 | 3.4076 | 100.0 | |
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| 0.0003 | 97.56 | 2000 | 3.4587 | 100.0 | |
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| 0.0001 | 121.95 | 2500 | 3.5256 | 100.0 | |
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| 0.0001 | 146.34 | 3000 | 3.5325 | 100.0 | |
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| 0.0001 | 170.73 | 3500 | 3.5419 | 100.0 | |
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| 0.0001 | 195.12 | 4000 | 3.5466 | 100.0 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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