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arabic_speech_ASR_Whisper

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  1. README.md +14 -9
  2. adapter_model.safetensors +1 -1
  3. runs/Mar07_10-31-50_8539dde49e16/events.out.tfevents.1709807510.8539dde49e16.2736.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -18,7 +18,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the common_voice_13_0 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4170
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.001
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- - train_batch_size: 6
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  - eval_batch_size: 8
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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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- - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.6558 | 1.0 | 1334 | 0.6054 |
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- | 0.4922 | 2.0 | 2668 | 0.5290 |
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- | 0.4324 | 3.0 | 4002 | 0.4767 |
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- | 0.3572 | 4.0 | 5336 | 0.4277 |
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- | 0.2179 | 5.0 | 6670 | 0.4170 |
 
 
 
 
 
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  ### Framework versions
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  - PEFT 0.9.0
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- - Transformers 4.38.1
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
 
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the common_voice_13_0 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6463
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.001
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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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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.7591 | 1.0 | 300 | 0.7290 |
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+ | 0.5736 | 2.0 | 600 | 0.6492 |
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+ | 0.4507 | 3.0 | 900 | 0.6266 |
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+ | 0.3456 | 4.0 | 1200 | 0.6130 |
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+ | 0.2947 | 5.0 | 1500 | 0.6018 |
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+ | 0.2153 | 6.0 | 1800 | 0.6061 |
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+ | 0.1761 | 7.0 | 2100 | 0.6146 |
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+ | 0.1185 | 8.0 | 2400 | 0.6290 |
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+ | 0.0808 | 9.0 | 2700 | 0.6381 |
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+ | 0.0643 | 10.0 | 3000 | 0.6463 |
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  ### Framework versions
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  - PEFT 0.9.0
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+ - Transformers 4.38.2
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
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