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--- |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- generated_from_trainer |
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datasets: |
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- PolyAI/minds14 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-tiny-ft-PolyAI-minds-14-enUS |
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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: PolyAI/minds14 |
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type: PolyAI/minds14 |
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config: en-US |
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split: train |
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args: en-US |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.3689492325855962 |
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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-ft-PolyAI-minds-14-enUS |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6365 |
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- Wer Ortho: 0.3763 |
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- Wer: 0.3689 |
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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: 4e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: constant_with_warmup |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 200 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
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| 2.9861 | 0.89 | 25 | 1.7468 | 0.5219 | 0.4038 | |
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| 0.8551 | 1.79 | 50 | 0.5897 | 0.8075 | 0.7928 | |
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| 0.3477 | 2.68 | 75 | 0.5229 | 0.6206 | 0.6198 | |
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| 0.151 | 3.57 | 100 | 0.5565 | 0.6971 | 0.6895 | |
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| 0.0895 | 4.46 | 125 | 0.5740 | 0.4812 | 0.4752 | |
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| 0.0373 | 5.36 | 150 | 0.5987 | 0.4479 | 0.4416 | |
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| 0.0232 | 6.25 | 175 | 0.6463 | 0.3751 | 0.3660 | |
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| 0.015 | 7.14 | 200 | 0.6365 | 0.3763 | 0.3689 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 1.12.1+cu116 |
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- Datasets 2.14.4 |
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- Tokenizers 0.12.1 |
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