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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-finetuned-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: 0.3624031007751938 |
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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-finetuned-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: 0.6785 |
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- Wer Ortho: 0.3607 |
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- Wer: 0.3624 |
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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: constant_with_warmup |
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- lr_scheduler_warmup_ratio: 0.1 |
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- lr_scheduler_warmup_steps: 50 |
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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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| 3.8342 | 1.0 | 28 | 2.7013 | 0.4859 | 0.3669 | |
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| 1.52 | 2.0 | 56 | 0.6447 | 0.3822 | 0.3624 | |
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| 0.4282 | 3.0 | 84 | 0.5154 | 0.3573 | 0.3521 | |
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| 0.2511 | 4.0 | 112 | 0.5017 | 0.3452 | 0.3430 | |
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| 0.1461 | 5.0 | 140 | 0.5106 | 0.3620 | 0.3572 | |
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| 0.0829 | 6.0 | 168 | 0.5399 | 0.3641 | 0.3592 | |
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| 0.0423 | 7.0 | 196 | 0.5596 | 0.3573 | 0.3527 | |
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| 0.0199 | 8.0 | 224 | 0.5846 | 0.3627 | 0.3598 | |
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| 0.0093 | 9.0 | 252 | 0.6006 | 0.3594 | 0.3572 | |
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| 0.0056 | 10.0 | 280 | 0.6207 | 0.3345 | 0.3301 | |
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| 0.0037 | 11.0 | 308 | 0.6238 | 0.3560 | 0.3534 | |
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| 0.0021 | 12.0 | 336 | 0.6377 | 0.3486 | 0.3482 | |
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| 0.0016 | 13.0 | 364 | 0.6485 | 0.3594 | 0.3579 | |
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| 0.0013 | 14.0 | 392 | 0.6621 | 0.3567 | 0.3572 | |
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| 0.0011 | 15.0 | 420 | 0.6617 | 0.3587 | 0.3605 | |
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| 0.0009 | 16.0 | 448 | 0.6682 | 0.3560 | 0.3559 | |
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| 0.0008 | 17.0 | 476 | 0.6741 | 0.3627 | 0.3624 | |
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| 0.0008 | 17.86 | 500 | 0.6785 | 0.3607 | 0.3624 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.1 |
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