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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 |
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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: 0.40436835891381345 |
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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 |
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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: 0.5951 |
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- Wer Ortho: 0.4781 |
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- Wer: 0.4044 |
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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-06 |
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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_steps: 50 |
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- training_steps: 600 |
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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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| 2.605 | 1.79 | 50 | 2.3450 | 0.5355 | 0.3967 | |
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| 1.67 | 3.57 | 100 | 1.4800 | 0.5355 | 0.4126 | |
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| 0.8205 | 5.36 | 150 | 0.8745 | 0.5836 | 0.4787 | |
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| 0.5984 | 7.14 | 200 | 0.7396 | 0.4923 | 0.4079 | |
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| 0.4993 | 8.93 | 250 | 0.6831 | 0.4769 | 0.3996 | |
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| 0.4134 | 10.71 | 300 | 0.6510 | 0.4830 | 0.4032 | |
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| 0.384 | 12.5 | 350 | 0.6307 | 0.4738 | 0.3961 | |
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| 0.3286 | 14.29 | 400 | 0.6162 | 0.4806 | 0.4050 | |
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| 0.3188 | 16.07 | 450 | 0.6062 | 0.4800 | 0.4050 | |
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| 0.2751 | 17.86 | 500 | 0.6010 | 0.4843 | 0.4097 | |
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| 0.2568 | 19.64 | 550 | 0.5970 | 0.4750 | 0.4026 | |
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| 0.237 | 21.43 | 600 | 0.5951 | 0.4781 | 0.4044 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.2 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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