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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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- AXAI/client |
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metrics: |
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- wer |
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base_model: openai/whisper-small |
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model-index: |
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- name: Whisper small 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: AXAI/client |
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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: 84.11458333333334 |
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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 small Ar - AxAI |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Client dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5990 |
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- Wer: 84.1146 |
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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: 2 |
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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: 16 |
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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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| 0.8044 | 6.37 | 200 | 1.2417 | 69.9219 | |
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| 0.036 | 12.75 | 400 | 1.1791 | 60.9375 | |
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| 0.0108 | 19.12 | 600 | 1.3128 | 80.2083 | |
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| 0.0035 | 25.5 | 800 | 1.3641 | 62.6953 | |
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| 0.0009 | 31.87 | 1000 | 1.4066 | 66.6016 | |
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| 0.0004 | 38.25 | 1200 | 1.4410 | 64.5833 | |
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| 0.0003 | 44.62 | 1400 | 1.4712 | 63.3464 | |
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| 0.0002 | 51.0 | 1600 | 1.4927 | 63.6068 | |
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| 0.0002 | 57.37 | 1800 | 1.5102 | 67.1875 | |
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| 0.0002 | 63.75 | 2000 | 1.5254 | 66.6016 | |
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| 0.0001 | 70.12 | 2200 | 1.5393 | 77.8646 | |
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| 0.0001 | 76.49 | 2400 | 1.5512 | 77.9297 | |
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| 0.0001 | 82.87 | 2600 | 1.5616 | 77.7344 | |
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| 0.0001 | 89.24 | 2800 | 1.5710 | 83.1380 | |
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| 0.0001 | 95.62 | 3000 | 1.5791 | 88.0859 | |
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| 0.0001 | 101.99 | 3200 | 1.5854 | 88.1510 | |
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| 0.0001 | 108.37 | 3400 | 1.5910 | 88.0859 | |
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| 0.0001 | 114.74 | 3600 | 1.5953 | 84.1146 | |
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| 0.0001 | 121.12 | 3800 | 1.5978 | 84.1797 | |
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| 0.0001 | 127.49 | 4000 | 1.5990 | 84.1146 | |
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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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