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--- |
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language: |
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- ko |
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license: apache-2.0 |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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base_model: openai/whisper-large |
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datasets: |
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- Marcusxx/gwanju |
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metrics: |
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- wer |
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model-index: |
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- name: gwanju_largeWER_model |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: Marcusxx/gwanju |
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type: Marcusxx/gwanju |
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args: 'config: ko, split: valid' |
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metrics: |
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- type: wer |
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value: 41.85458286890166 |
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name: Wer |
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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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# gwanju_largeWER_model |
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This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co./openai/whisper-large) on the Marcusxx/gwanju dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3334 |
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- Wer: 41.8546 |
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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: 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_steps: 100 |
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- training_steps: 4000 |
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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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| 0.4683 | 0.0741 | 250 | 0.4884 | 104.4328 | |
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| 0.4578 | 0.1482 | 500 | 0.4522 | 55.8304 | |
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| 0.4675 | 0.2223 | 750 | 0.4379 | 65.3948 | |
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| 0.4338 | 0.2964 | 1000 | 0.4225 | 65.4206 | |
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| 0.4547 | 0.3705 | 1250 | 0.4023 | 63.5814 | |
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| 0.3676 | 0.4446 | 1500 | 0.3914 | 47.9551 | |
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| 0.3752 | 0.5187 | 1750 | 0.3840 | 48.3838 | |
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| 0.3584 | 0.5928 | 2000 | 0.3745 | 44.8641 | |
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| 0.4221 | 0.6669 | 2250 | 0.3638 | 42.4548 | |
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| 0.3432 | 0.7410 | 2500 | 0.3563 | 42.7206 | |
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| 0.3993 | 0.8151 | 2750 | 0.3497 | 44.7955 | |
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| 0.3448 | 0.8892 | 3000 | 0.3437 | 43.3722 | |
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| 0.3441 | 0.9632 | 3250 | 0.3381 | 40.4270 | |
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| 0.2317 | 1.0373 | 3500 | 0.3350 | 39.5782 | |
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| 0.2063 | 1.1114 | 3750 | 0.3339 | 40.8385 | |
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| 0.2016 | 1.1855 | 4000 | 0.3334 | 41.8546 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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