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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-hac |
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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 hawrami |
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type: razhan/DOLMA-speech |
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args: hawrami |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.47917770477906113 |
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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-hac |
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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 hawrami dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3272 |
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- Wer: 0.4792 |
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- Cer: 0.1039 |
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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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| 1.9468 | 1.0 | 27 | 0.9999 | 0.9633 | 0.3797 | |
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| 0.6132 | 2.0 | 54 | 0.4681 | 0.6078 | 0.1469 | |
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| 0.3976 | 3.0 | 81 | 0.3668 | 0.5161 | 0.1128 | |
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| 0.3485 | 4.0 | 108 | 0.3360 | 0.4889 | 0.1065 | |
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| 0.3292 | 5.0 | 135 | 0.3272 | 0.4792 | 0.1039 | |
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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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