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--- |
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library_name: transformers |
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language: |
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- ne |
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license: apache-2.0 |
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base_model: openai/whisper-large-v3 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- kiranpantha/OpenSLR54-Balanced-Nepali |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large v3 Nepali - Kiran Pantha |
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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: OpenSLR54 |
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type: kiranpantha/OpenSLR54-Balanced-Nepali |
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config: default |
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split: test |
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args: 'config: ne, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 18.72503840245776 |
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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 Large v3 Nepali - Kiran Pantha |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the OpenSLR54 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0876 |
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- Wer: 18.7250 |
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- Cer: 4.4861 |
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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: 8 |
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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: 5000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
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|:-------------:|:------:|:----:|:-------:|:---------------:|:-------:| |
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| 0.2266 | 0.1200 | 300 | 11.9034 | 0.2345 | 44.7619 | |
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| 0.208 | 0.2399 | 600 | 11.3157 | 0.2132 | 41.1060 | |
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| 0.185 | 0.3599 | 900 | 9.4204 | 0.1753 | 35.6068 | |
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| 0.1567 | 0.4798 | 1200 | 8.8596 | 0.1634 | 33.9324 | |
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| 0.1411 | 0.5998 | 1500 | 8.7004 | 0.1523 | 33.0568 | |
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| 0.1377 | 0.7197 | 1800 | 7.3120 | 0.1371 | 29.7849 | |
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| 0.1147 | 0.8397 | 2100 | 7.0010 | 0.1332 | 27.7112 | |
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| 0.1116 | 0.9596 | 2400 | 6.5798 | 0.1212 | 26.3287 | |
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| 0.0757 | 1.0796 | 2700 | 6.1268 | 0.1193 | 24.7773 | |
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| 0.0609 | 1.1995 | 3000 | 5.8991 | 0.1154 | 24.6237 | |
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| 0.0612 | 1.3195 | 3300 | 5.2599 | 0.1091 | 22.0737 | |
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| 0.0627 | 1.4394 | 3600 | 5.3579 | 0.1045 | 21.6283 | |
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| 0.0582 | 1.5594 | 3900 | 5.1938 | 0.0995 | 21.5054 | |
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| 0.0551 | 1.6793 | 4200 | 4.7947 | 0.0956 | 19.8771 | |
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| 0.052 | 1.7993 | 4500 | 4.5473 | 0.0897 | 19.1244 | |
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| 0.0438 | 1.9192 | 4800 | 4.4861 | 0.0876 | 18.7250 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cxx11.abi |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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