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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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- Ussen/swc-drc-kat
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metrics:
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- wer
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model-index:
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- name: whisper-medium-swc-drc-kat-1
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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: Ussen/swc-drc-kat
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type: Ussen/swc-drc-kat
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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: 0.49379203310915676
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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-swc-drc-kat-1
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Ussen/swc-drc-kat dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9701
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- Wer Ortho: 50.0388
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- Wer: 0.4938
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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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| 0.6769 | 2.96 | 1000 | 0.8341 | 51.2296 | 0.5072 |
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| 0.365 | 5.93 | 2000 | 0.8083 | 49.3917 | 0.4876 |
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| 0.165 | 8.89 | 3000 | 0.8806 | 51.3073 | 0.5067 |
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| 0.059 | 11.85 | 4000 | 0.9701 | 50.0388 | 0.4938 |
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### Framework versions
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- Transformers 4.32.0.dev0
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.3
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- Tokenizers 0.13.3
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