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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-large-v3
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tags:
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- generated_from_trainer
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datasets:
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- pranetk/paraspeak-data-v3
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metrics:
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- wer
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model-index:
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- name: Whisper Large V3 Paraspeak V2
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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: Paraspeak Dataset 3.0
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type: pranetk/paraspeak-data-v3
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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: 62.121212121212125
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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 Paraspeak V2
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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 Paraspeak Dataset 3.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0662
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- Wer: 62.1212
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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: 3e-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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- training_steps: 1000
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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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| 0.1361 | 2.9412 | 50 | 0.8743 | 77.2727 |
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| 0.0603 | 5.8824 | 100 | 1.0115 | 65.1515 |
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| 0.0452 | 8.8235 | 150 | 1.0837 | 71.2121 |
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| 0.0042 | 11.7647 | 200 | 1.0400 | 78.7879 |
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| 0.023 | 14.7059 | 250 | 1.0296 | 71.2121 |
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| 0.0023 | 17.6471 | 300 | 0.9761 | 69.6970 |
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| 0.0005 | 20.5882 | 350 | 1.0758 | 71.2121 |
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| 0.0098 | 23.5294 | 400 | 1.1036 | 71.2121 |
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| 0.0006 | 26.4706 | 450 | 1.0662 | 65.1515 |
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| 0.0001 | 29.4118 | 500 | 1.0563 | 62.1212 |
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| 0.0 | 32.3529 | 550 | 1.0521 | 62.1212 |
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| 0.0 | 35.2941 | 600 | 1.0541 | 62.1212 |
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| 0.0 | 38.2353 | 650 | 1.0563 | 62.1212 |
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| 0.0 | 41.1765 | 700 | 1.0587 | 62.1212 |
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| 0.0 | 44.1176 | 750 | 1.0609 | 62.1212 |
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| 0.0 | 47.0588 | 800 | 1.0628 | 62.1212 |
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| 0.0 | 50.0 | 850 | 1.0641 | 62.1212 |
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| 0.0 | 52.9412 | 900 | 1.0653 | 62.1212 |
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| 0.0 | 55.8824 | 950 | 1.0659 | 62.1212 |
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| 0.0 | 58.8235 | 1000 | 1.0662 | 62.1212 |
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### Framework versions
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- Transformers 4.42.3
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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