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---
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language:
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- zh
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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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- edmundchan70/Cantonese_fine_tune
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metrics:
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- wer
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model-index:
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- name: Whisper Small fine tune-Edmund-0818
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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: Preach_speech_finetuning
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type: edmundchan70/Cantonese_fine_tune
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config: default
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split: train
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args: 'config: chinese, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 30.476190476190478
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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 Small fine tune-Edmund-0818
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Preach_speech_finetuning dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1966
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- Wer: 30.4762
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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: 1.25e-05
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- train_batch_size: 16
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- eval_batch_size: 8
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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_ratio: 0.1
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- num_epochs: 15
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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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| No log | 1.0 | 156 | 0.1196 | 17.1429 |
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| No log | 2.0 | 312 | 0.1553 | 24.6032 |
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| No log | 3.0 | 468 | 0.1655 | 26.5079 |
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| 0.0806 | 4.0 | 624 | 0.1820 | 29.5238 |
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| 0.0806 | 5.0 | 780 | 0.1792 | 30.1587 |
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| 0.0806 | 6.0 | 936 | 0.1998 | 31.5873 |
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| 0.0131 | 7.0 | 1092 | 0.1954 | 31.2698 |
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| 0.0131 | 8.0 | 1248 | 0.1923 | 30.6349 |
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| 0.0131 | 9.0 | 1404 | 0.1905 | 31.2698 |
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| 0.0016 | 10.0 | 1560 | 0.1954 | 31.2698 |
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| 0.0016 | 11.0 | 1716 | 0.1931 | 31.1111 |
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| 0.0016 | 12.0 | 1872 | 0.1953 | 30.4762 |
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| 0.0005 | 13.0 | 2028 | 0.1960 | 30.6349 |
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| 0.0005 | 14.0 | 2184 | 0.1964 | 30.6349 |
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| 0.0005 | 15.0 | 2340 | 0.1966 | 30.4762 |
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### Framework versions
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- Transformers 4.44.0
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- Pytorch 2.4.0+cu124
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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