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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-finetune-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[450:] |
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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: 0.3382526564344746 |
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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-finetune-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: 0.6541 |
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- Wer Ortho: 0.3399 |
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- Wer: 0.3383 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 50 |
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- training_steps: 1000 |
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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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| 0.3136 | 3.57 | 100 | 0.4883 | 0.3640 | 0.3524 | |
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| 0.0417 | 7.14 | 200 | 0.5146 | 0.3560 | 0.3442 | |
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| 0.0066 | 10.71 | 300 | 0.5736 | 0.3411 | 0.3353 | |
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| 0.0017 | 14.29 | 400 | 0.6040 | 0.3455 | 0.3418 | |
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| 0.0013 | 17.86 | 500 | 0.6226 | 0.3393 | 0.3365 | |
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| 0.0009 | 21.43 | 600 | 0.6352 | 0.3393 | 0.3365 | |
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| 0.0007 | 25.0 | 700 | 0.6436 | 0.3399 | 0.3371 | |
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| 0.0006 | 28.57 | 800 | 0.6492 | 0.3399 | 0.3383 | |
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| 0.0006 | 32.14 | 900 | 0.6530 | 0.3399 | 0.3383 | |
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| 0.0006 | 35.71 | 1000 | 0.6541 | 0.3399 | 0.3383 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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