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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[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: 0.3252656434474616 |
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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: 0.8008 |
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- Wer Ortho: 0.3523 |
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- Wer: 0.3253 |
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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: 4 |
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- seed: 42 |
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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: constant_with_warmup |
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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 500 |
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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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| 1.593 | 1.79 | 50 | 1.0054 | 0.5003 | 0.4185 | |
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| 0.3982 | 3.57 | 100 | 0.7250 | 0.4121 | 0.3554 | |
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| 0.2075 | 5.36 | 150 | 0.6898 | 0.4226 | 0.3518 | |
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| 0.0957 | 7.14 | 200 | 0.6909 | 0.4028 | 0.3371 | |
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| 0.0412 | 8.93 | 250 | 0.7296 | 0.3695 | 0.3300 | |
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| 0.0186 | 10.71 | 300 | 0.7522 | 0.3627 | 0.3270 | |
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| 0.008 | 12.5 | 350 | 0.7703 | 0.3584 | 0.3288 | |
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| 0.0049 | 14.29 | 400 | 0.7756 | 0.3553 | 0.3294 | |
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| 0.0032 | 16.07 | 450 | 0.7889 | 0.3516 | 0.3235 | |
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| 0.0023 | 17.86 | 500 | 0.8008 | 0.3523 | 0.3253 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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