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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-PolyAI-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: 0.36068476977567887 |
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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-PolyAI-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: 0.5565 |
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- Wer Ortho: 0.5120 |
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- Wer: 0.3607 |
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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-07 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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: 50 |
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- training_steps: 4000 |
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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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| 2.3523 | 71.43 | 500 | 2.3552 | 0.6089 | 0.4067 | |
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| 1.1267 | 142.86 | 1000 | 1.2038 | 0.5922 | 0.4132 | |
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| 0.5363 | 214.29 | 1500 | 0.7055 | 0.5694 | 0.4014 | |
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| 0.3846 | 285.71 | 2000 | 0.6171 | 0.5490 | 0.4008 | |
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| 0.304 | 357.14 | 2500 | 0.5816 | 0.5379 | 0.3890 | |
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| 0.2428 | 428.57 | 3000 | 0.5644 | 0.5182 | 0.3713 | |
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| 0.1922 | 500.0 | 3500 | 0.5570 | 0.5139 | 0.3666 | |
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| 0.1499 | 571.43 | 4000 | 0.5565 | 0.5120 | 0.3607 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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