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---
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language:
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- th
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license: apache-2.0
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base_model: openai/whisper-small
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tags:
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- generated_from_trainer
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datasets:
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- fruk19/N_asr
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metrics:
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- wer
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model-index:
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- name: North_asri
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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: aicookcook
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type: fruk19/N_asr
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args: 'config: th'
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metrics:
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- name: Wer
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type: wer
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value: 6.260140616549487
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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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# North_asri
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the aicookcook dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0739
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- Wer: 6.2601
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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: 4
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- eval_batch_size: 4
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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: linear
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- lr_scheduler_warmup_steps: 99
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- num_epochs: 3
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|
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| 0.099 | 1.0 | 3000 | 0.1002 | 10.8545 |
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| 0.0342 | 2.0 | 6000 | 0.0776 | 7.1390 |
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| 0.0098 | 3.0 | 9000 | 0.0739 | 6.2601 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.0.1+cu117
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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