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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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