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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-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-en-US
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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-AU
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split: train
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args: en-AU
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metrics:
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- name: Wer
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type: wer
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value: 0.20146619603584034
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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-US
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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: 0.6756
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- Wer Ortho: 0.2044
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- Wer: 0.2015
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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_steps: 50
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- training_steps: 4000
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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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| 0.0007 | 17.86 | 500 | 0.5138 | 0.1941 | 0.1920 |
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| 0.0002 | 35.71 | 1000 | 0.5565 | 0.1958 | 0.1936 |
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| 0.0001 | 53.57 | 1500 | 0.5851 | 0.1981 | 0.1958 |
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| 0.0001 | 71.43 | 2000 | 0.6081 | 0.2030 | 0.1998 |
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| 0.0 | 89.29 | 2500 | 0.6273 | 0.2038 | 0.2009 |
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| 0.0 | 107.14 | 3000 | 0.6441 | 0.2021 | 0.1996 |
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| 0.0 | 125.0 | 3500 | 0.6602 | 0.2035 | 0.2007 |
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| 0.0 | 142.86 | 4000 | 0.6756 | 0.2044 | 0.2015 |
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### Framework versions
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- Transformers 4.31.0.dev0
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- Pytorch 1.12.1+cu116
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- Datasets 2.4.0
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- Tokenizers 0.12.1
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