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--- |
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language: |
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- hi |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- generated_from_trainer |
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datasets: |
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- velocity-whisper-tiny |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-tiny-finetuned-hinglish |
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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: whisper-training |
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type: velocity-whisper-tiny |
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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: 42.262816735415434 |
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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-tiny-finetuned-hinglish |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the whisper-training dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7758 |
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- Wer: 42.2628 |
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 40 |
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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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| 0.3632 | 1.7825 | 1000 | 0.3962 | 51.0784 | |
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| 0.2411 | 3.5651 | 2000 | 0.3428 | 45.1149 | |
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| 0.1242 | 5.3476 | 3000 | 0.3459 | 42.1685 | |
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| 0.0813 | 7.1301 | 4000 | 0.3610 | 42.1685 | |
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| 0.0654 | 8.9127 | 5000 | 0.3949 | 41.9210 | |
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| 0.0309 | 10.6952 | 6000 | 0.4422 | 42.7814 | |
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| 0.0161 | 12.4777 | 7000 | 0.4836 | 42.3925 | |
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| 0.0067 | 14.2602 | 8000 | 0.5291 | 42.9346 | |
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| 0.0032 | 16.0428 | 9000 | 0.5645 | 42.4514 | |
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| 0.0031 | 17.8253 | 10000 | 0.5951 | 42.7814 | |
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| 0.002 | 19.6078 | 11000 | 0.6248 | 42.5103 | |
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| 0.0007 | 21.3904 | 12000 | 0.6486 | 42.8167 | |
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| 0.0004 | 23.1729 | 13000 | 0.6760 | 42.0625 | |
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| 0.0008 | 24.9554 | 14000 | 0.6982 | 42.4396 | |
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| 0.0018 | 26.7380 | 15000 | 0.7149 | 42.4985 | |
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| 0.0002 | 28.5205 | 16000 | 0.7172 | 41.8739 | |
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| 0.0001 | 30.3030 | 17000 | 0.7307 | 42.4042 | |
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| 0.0001 | 32.0856 | 18000 | 0.7399 | 42.0742 | |
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| 0.0001 | 33.8681 | 19000 | 0.7497 | 42.1332 | |
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| 0.0001 | 35.6506 | 20000 | 0.7608 | 42.0860 | |
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| 0.0 | 37.4332 | 21000 | 0.7695 | 41.9682 | |
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| 0.0 | 39.2157 | 22000 | 0.7758 | 42.2628 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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