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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-small |
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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 Small |
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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: 11.272359095511305 |
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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 Small |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Fyp Dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1965 |
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- Wer: 11.2724 |
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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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- 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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- training_steps: 102 |
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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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| 0.1398 | 0.4 | 20 | 0.2211 | 13.1623 | |
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| 0.0941 | 0.8 | 40 | 0.2144 | 11.8124 | |
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| 0.048 | 1.2 | 60 | 0.1997 | 11.2386 | |
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| 0.0481 | 1.6 | 80 | 0.1979 | 11.3736 | |
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| 0.0337 | 2.0 | 100 | 0.1965 | 11.2724 | |
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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 2.20.0 |
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- Tokenizers 0.19.1 |
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