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--- |
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license: apache-2.0 |
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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-en |
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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: 34.120425029515935 |
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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-en |
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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: 0.6900 |
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- Wer Ortho: 35.9038 |
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- Wer: 34.1204 |
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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: 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: linear |
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- lr_scheduler_warmup_steps: 150 |
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- training_steps: 500 |
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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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| 3.5847 | 1.79 | 50 | 2.5796 | 52.3751 | 40.2597 | |
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| 0.6921 | 3.57 | 100 | 0.6884 | 42.5663 | 37.1901 | |
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| 0.305 | 5.36 | 150 | 0.5833 | 39.1733 | 35.5962 | |
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| 0.1133 | 7.14 | 200 | 0.5980 | 36.8291 | 34.3566 | |
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| 0.0391 | 8.93 | 250 | 0.6228 | 37.3843 | 34.2385 | |
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| 0.0138 | 10.71 | 300 | 0.6522 | 39.4201 | 37.1311 | |
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| 0.0051 | 12.5 | 350 | 0.6699 | 35.7187 | 33.4711 | |
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| 0.0032 | 14.29 | 400 | 0.6826 | 36.0888 | 34.0024 | |
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| 0.0027 | 16.07 | 450 | 0.6881 | 36.2122 | 34.3566 | |
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| 0.0024 | 17.86 | 500 | 0.6900 | 35.9038 | 34.1204 | |
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### Framework versions |
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- Transformers 4.29.0.dev0 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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