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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- razhan/DOLMA-speech |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-base-sdh |
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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: razhan/DOLMA-speech southern_kurdish |
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type: razhan/DOLMA-speech |
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args: southern_kurdish |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.6882181444006173 |
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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-base-sdh |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the razhan/DOLMA-speech southern_kurdish dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6611 |
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- Wer: 0.6882 |
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- Cer: 0.2165 |
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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: 192 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 384 |
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- total_eval_batch_size: 256 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 1 |
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- num_epochs: 5.0 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 3.8394 | 1.0 | 16 | 1.9696 | 0.9849 | 0.6163 | |
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| 1.3507 | 2.0 | 32 | 1.0906 | 0.8956 | 0.4107 | |
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| 0.9898 | 3.0 | 48 | 0.7982 | 0.7872 | 0.2881 | |
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| 0.6834 | 4.0 | 64 | 0.6941 | 0.7153 | 0.2266 | |
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| 0.5981 | 5.0 | 80 | 0.6611 | 0.6882 | 0.2165 | |
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### Framework versions |
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- Transformers 4.49.0.dev0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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