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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: mit |
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base_model: openai/whisper-large-v3-turbo |
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tags: |
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- generated_from_trainer |
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datasets: |
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- kiranpantha/OpenSLR54-Whisper |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large v3 Turbo 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-Whisper |
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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: 23.63425925925926 |
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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 Turbo Nepali - Kiran Pantha |
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This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the OpenSLR54 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1707 |
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- Wer: 23.6343 |
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- Cer: 5.4903 |
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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 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 | Validation Loss | Wer | Cer | |
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|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:| |
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| 0.3073 | 0.3597 | 300 | 0.2895 | 53.2870 | 13.5643 | |
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| 0.2457 | 0.7194 | 600 | 0.2396 | 45.3704 | 11.6816 | |
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| 0.166 | 1.0791 | 900 | 0.2062 | 37.9167 | 9.6668 | |
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| 0.1477 | 1.4388 | 1200 | 0.1949 | 37.4306 | 9.3071 | |
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| 0.1284 | 1.7986 | 1500 | 0.1680 | 32.6620 | 8.3235 | |
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| 0.0745 | 2.1583 | 1800 | 0.1706 | 31.1574 | 7.5272 | |
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| 0.0701 | 2.5180 | 2100 | 0.1661 | 32.0370 | 7.7217 | |
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| 0.0777 | 2.8777 | 2400 | 0.1599 | 28.6111 | 7.1308 | |
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| 0.0455 | 3.2374 | 2700 | 0.1723 | 28.7037 | 7.0097 | |
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| 0.0375 | 3.5971 | 3000 | 0.1579 | 26.9444 | 6.3674 | |
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| 0.0374 | 3.9568 | 3300 | 0.1639 | 26.8981 | 6.2794 | |
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| 0.0171 | 4.3165 | 3600 | 0.1711 | 25.3241 | 6.2280 | |
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| 0.0219 | 4.6763 | 3900 | 0.1638 | 25.0 | 5.9307 | |
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| 0.0089 | 5.0360 | 4200 | 0.1635 | 24.5139 | 5.7435 | |
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| 0.0072 | 5.3957 | 4500 | 0.1717 | 24.1898 | 5.5711 | |
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| 0.0059 | 5.7554 | 4800 | 0.1707 | 23.6343 | 5.4903 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.5.1+cxx11.abi |
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- Datasets 3.2.0 |
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- Tokenizers 0.20.3 |
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