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update model card README.md
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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-medium
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tags:
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- generated_from_trainer
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datasets:
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- BrainTheos/ojpl
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metrics:
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- wer
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model-index:
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- name: whisper-medium-ln-ojpl-2
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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: BrainTheos/ojpl
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type: BrainTheos/ojpl
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config: default
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split: train
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args: default
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metrics:
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- name: Wer
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type: wer
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value: 0.29010989010989013
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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-medium-ln-ojpl-2
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the BrainTheos/ojpl dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1202
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- Wer Ortho: 35.8309
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- Wer: 0.2901
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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: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 8
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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: 500
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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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| 0.0172 | 23.19 | 1000 | 0.9966 | 41.9139 | 0.3407 |
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| 0.0053 | 46.38 | 2000 | 1.0716 | 37.0920 | 0.2996 |
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| 0.0034 | 69.57 | 3000 | 1.1329 | 36.0163 | 0.2850 |
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| 0.0021 | 92.75 | 4000 | 1.1202 | 35.8309 | 0.2901 |
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### Framework versions
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- Transformers 4.32.0.dev0
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- Pytorch 1.13.1+cu117
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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