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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-minds14 |
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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: 0.33412042502951594 |
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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-minds14 |
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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: 0.4866 |
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- Wer Ortho: 0.3356 |
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- Wer: 0.3341 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 5 |
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- training_steps: 50 |
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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 Ortho | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
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| 3.8369 | 0.36 | 5 | 2.6069 | 0.5200 | 0.4044 | |
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| 1.9739 | 0.71 | 10 | 1.0073 | 0.4411 | 0.4026 | |
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| 0.728 | 1.07 | 15 | 0.6096 | 0.3948 | 0.3902 | |
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| 0.3929 | 1.43 | 20 | 0.5288 | 0.4503 | 0.4486 | |
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| 0.4044 | 1.79 | 25 | 0.4995 | 0.3430 | 0.3430 | |
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| 0.311 | 2.14 | 30 | 0.4772 | 0.3701 | 0.3701 | |
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| 0.2404 | 2.5 | 35 | 0.4738 | 0.3134 | 0.3135 | |
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| 0.1688 | 2.86 | 40 | 0.4700 | 0.3257 | 0.3253 | |
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| 0.1278 | 3.21 | 45 | 0.4748 | 0.3183 | 0.3164 | |
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| 0.0775 | 3.57 | 50 | 0.4866 | 0.3356 | 0.3341 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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