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--- |
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library_name: transformers |
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language: |
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- ko |
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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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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- whsNect/__g__d___ |
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metrics: |
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- wer |
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model-index: |
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- name: __g__d____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: whsNect/__g__d___ |
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type: whsNect/__g__d___ |
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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: 8.460209304600138 |
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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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# __g__d____model |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the whsNect/__g__d___ dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0502 |
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- Wer: 8.4602 |
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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: 5e-06 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Use adamw_bnb_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 15000 |
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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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| 0.0361 | 1.6722 | 500 | 0.0385 | 9.2003 | |
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| 0.0099 | 3.3445 | 1000 | 0.0313 | 5.2457 | |
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| 0.006 | 5.0167 | 1500 | 0.0335 | 6.3769 | |
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| 0.003 | 6.6890 | 2000 | 0.0348 | 4.8773 | |
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| 0.0021 | 8.3612 | 2500 | 0.0351 | 17.5822 | |
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| 0.0013 | 10.0334 | 3000 | 0.0369 | 5.0892 | |
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| 0.0016 | 11.7057 | 3500 | 0.0371 | 10.6837 | |
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| 0.0011 | 13.3779 | 4000 | 0.0367 | 5.8716 | |
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| 0.0014 | 15.0502 | 4500 | 0.0385 | 46.1350 | |
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| 0.0008 | 16.7224 | 5000 | 0.0408 | 10.2338 | |
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| 0.0006 | 18.3946 | 5500 | 0.0400 | 9.9077 | |
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| 0.0007 | 20.0669 | 6000 | 0.0410 | 11.2053 | |
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| 0.0003 | 21.7391 | 6500 | 0.0414 | 22.9192 | |
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| 0.0002 | 23.4114 | 7000 | 0.0415 | 17.6768 | |
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| 0.0009 | 25.0836 | 7500 | 0.0420 | 22.1074 | |
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| 0.0005 | 26.7559 | 8000 | 0.0440 | 14.8828 | |
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| 0.0005 | 28.4281 | 8500 | 0.0417 | 10.4065 | |
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| 0.0001 | 30.1003 | 9000 | 0.0441 | 20.4545 | |
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| 0.0001 | 31.7726 | 9500 | 0.0453 | 9.3176 | |
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| 0.0001 | 33.4448 | 10000 | 0.0460 | 11.3553 | |
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| 0.0001 | 35.1171 | 10500 | 0.0466 | 10.9999 | |
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| 0.0001 | 36.7893 | 11000 | 0.0471 | 11.0749 | |
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| 0.0001 | 38.4615 | 11500 | 0.0479 | 12.3887 | |
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| 0.0 | 40.1338 | 12000 | 0.0483 | 10.3413 | |
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| 0.0 | 41.8060 | 12500 | 0.0487 | 8.3363 | |
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| 0.0001 | 43.4783 | 13000 | 0.0491 | 8.6852 | |
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| 0.0 | 45.1505 | 13500 | 0.0495 | 7.7462 | |
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| 0.0 | 46.8227 | 14000 | 0.0499 | 8.1472 | |
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| 0.0 | 48.4950 | 14500 | 0.0501 | 7.9516 | |
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| 0.0 | 50.1672 | 15000 | 0.0502 | 8.4602 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 3.4.1 |
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- Tokenizers 0.21.1 |
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