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--- |
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library_name: transformers |
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language: |
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- id |
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license: apache-2.0 |
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base_model: kneth90/whisper-small-id-kp |
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tags: |
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- generated_from_trainer |
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datasets: |
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- kneth90/snamol_temp |
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metrics: |
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- wer |
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model-index: |
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- name: WHISPER Small KP |
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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: Common Voice 11.0 |
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type: kneth90/snamol_temp |
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args: 'config: hi, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 814.2857142857142 |
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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 KP |
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This model is a fine-tuned version of [kneth90/whisper-small-id-kp](https://huggingface.co/kneth90/whisper-small-id-kp) on the Common Voice 11.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4420 |
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- Wer: 814.2857 |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.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: 500 |
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- training_steps: 6000 |
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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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| 0.0 | 1000.0 | 1000 | 0.5975 | 7.1429 | |
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| 0.0 | 2000.0 | 2000 | 0.8193 | 14.2857 | |
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| 0.0 | 3000.0 | 3000 | 1.0415 | 50.0 | |
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| 0.0 | 4000.0 | 4000 | 1.3226 | 50.0 | |
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| 0.0 | 5000.0 | 5000 | 1.3835 | 42.8571 | |
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| 0.0 | 6000.0 | 6000 | 1.4420 | 814.2857 | |
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### Framework versions |
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- Transformers 4.48.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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