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--- |
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language: |
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- tr |
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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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datasets: |
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- synthesized_squad |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Synthesized Turkish |
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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: synthesized_squad |
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type: synthesized_squad |
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config: null |
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split: None |
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args: 'config: hi, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 13.726700407357118 |
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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 Synthesized Turkish |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the synthesized_squad dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2564 |
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- Wer: 13.7267 |
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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: 500 |
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- training_steps: 2000 |
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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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| 1.276 | 1.04 | 100 | 0.5859 | 92.8836 | |
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| 0.436 | 2.08 | 200 | 0.3916 | 19.5285 | |
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| 0.218 | 3.12 | 300 | 0.2345 | 13.2453 | |
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| 0.0903 | 4.17 | 400 | 0.2332 | 12.9737 | |
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| 0.0517 | 5.21 | 500 | 0.2360 | 14.3439 | |
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| 0.0302 | 6.25 | 600 | 0.2318 | 14.0415 | |
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| 0.0223 | 7.29 | 700 | 0.2372 | 13.9674 | |
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| 0.0085 | 8.33 | 800 | 0.2421 | 12.4738 | |
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| 0.0084 | 9.38 | 900 | 0.2424 | 12.3750 | |
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| 0.0043 | 10.42 | 1000 | 0.2421 | 12.8935 | |
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| 0.0034 | 11.46 | 1100 | 0.2478 | 13.6218 | |
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| 0.0025 | 12.5 | 1200 | 0.2490 | 14.7327 | |
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| 0.002 | 13.54 | 1300 | 0.2513 | 13.0910 | |
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| 0.0019 | 14.58 | 1400 | 0.2521 | 13.2453 | |
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| 0.0013 | 15.62 | 1500 | 0.2532 | 13.2144 | |
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| 0.0012 | 16.67 | 1600 | 0.2547 | 13.3132 | |
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| 0.001 | 17.71 | 1700 | 0.2552 | 13.7514 | |
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| 0.001 | 18.75 | 1800 | 0.2559 | 13.7452 | |
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| 0.001 | 19.79 | 1900 | 0.2563 | 13.7514 | |
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| 0.001 | 20.83 | 2000 | 0.2564 | 13.7267 | |
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### Framework versions |
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- Transformers 4.28.0.dev0 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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