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README.md
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---
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license: apache-2.0
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base_model: openai/whisper-small
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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-Handy-Pretty - ckandemir
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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: 0.3116883116883117
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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-Handy-Pretty - ckandemir
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the PolyAI/minds14 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5197
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- Wer Ortho: 31.6471
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- Wer: 0.3117
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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: 5e-05
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- train_batch_size: 12
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- eval_batch_size: 12
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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: cosine_with_restarts
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- lr_scheduler_warmup_steps: 100
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- training_steps: 150
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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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| 0.8427 | 1.32 | 50 | 0.5401 | 35.9655 | 0.3566 |
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| 0.1982 | 2.63 | 100 | 0.5179 | 35.5336 | 0.3501 |
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| 0.0531 | 3.95 | 150 | 0.5197 | 31.6471 | 0.3117 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.1
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- Tokenizers 0.13.3
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