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--- |
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library_name: transformers |
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language: |
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- en |
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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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- lord-reso/inbrowser-proctor-dataset |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper-Small-Inbrowser-Proctor |
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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: Inbrowser Procotor Dataset |
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type: lord-reso/inbrowser-proctor-dataset |
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args: 'config: en, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 17.075501752150366 |
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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-Small-Inbrowser-Proctor |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Inbrowser Procotor Dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3099 |
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- Wer: 17.0755 |
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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: 5e-06 |
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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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- 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: 25 |
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- training_steps: 250 |
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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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| 0.3461 | 0.4545 | 25 | 0.4545 | 26.0433 | |
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| 0.1902 | 0.9091 | 50 | 0.3309 | 17.4419 | |
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| 0.1184 | 1.3636 | 75 | 0.3120 | 14.6543 | |
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| 0.0944 | 1.8182 | 100 | 0.3066 | 16.7251 | |
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| 0.0632 | 2.2727 | 125 | 0.3046 | 14.8455 | |
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| 0.0688 | 2.7273 | 150 | 0.3060 | 14.8933 | |
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| 0.0479 | 3.1818 | 175 | 0.3063 | 17.1074 | |
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| 0.0515 | 3.6364 | 200 | 0.3081 | 15.4986 | |
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| 0.0296 | 4.0909 | 225 | 0.3096 | 17.2507 | |
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| 0.0348 | 4.5455 | 250 | 0.3099 | 17.0755 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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