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--- |
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language: |
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- eng |
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license: apache-2.0 |
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base_model: openai/whisper-base.en |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fyp |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Fine tuned Base |
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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: Fyp Dataset |
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type: fyp |
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args: 'config: eng, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 15.01856226797165 |
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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 Fine tuned Base |
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This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the Fyp Dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3550 |
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- Wer: 15.0186 |
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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: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 5 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 2 |
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- num_epochs: 3 |
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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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| 0.3123 | 0.5 | 25 | 0.4652 | 20.1147 | |
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| 0.3282 | 1.0 | 50 | 0.3655 | 16.2673 | |
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| 0.0376 | 1.5 | 75 | 0.3693 | 15.4573 | |
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| 0.0468 | 2.0 | 100 | 0.3754 | 20.2497 | |
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| 0.0067 | 2.5 | 125 | 0.3585 | 15.3898 | |
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| 0.0098 | 3.0 | 150 | 0.3550 | 15.0186 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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