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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-minds-v5-numproc1
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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[451:]
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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: 0.37507453786523554
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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-minds-v5-numproc1
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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: 0.6530
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- Wer Ortho: 0.4102
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- Wer: 0.3751
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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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- 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: 100
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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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| 0.4354 | 3.57 | 100 | 0.5542 | 0.4539 | 0.3870 |
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| 0.066 | 7.14 | 200 | 0.5501 | 0.4059 | 0.3554 |
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| 0.0086 | 10.71 | 300 | 0.6204 | 0.3953 | 0.3542 |
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| 0.0028 | 14.29 | 400 | 0.6455 | 0.3990 | 0.3631 |
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| 0.0022 | 17.86 | 500 | 0.6530 | 0.4102 | 0.3751 |
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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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