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--- |
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language: |
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- uz |
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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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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_1 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium UZ - Bahriddin Mo'minov |
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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: Common Voice 16.1 |
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type: mozilla-foundation/common_voice_16_1 |
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config: uz |
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split: test |
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args: 'config: uz, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 17.28008879695265 |
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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 Medium UZ - Bahriddin Mo'minov |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 16.1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2593 |
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- Wer: 17.2801 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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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- num_epochs: 5 |
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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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| 0.4581 | 0.2641 | 1000 | 0.3953 | 30.3663 | |
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| 0.3859 | 0.5282 | 2000 | 0.3257 | 26.6366 | |
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| 0.2601 | 0.7923 | 3000 | 0.2745 | 22.5373 | |
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| 0.1724 | 1.0564 | 4000 | 0.2611 | 21.4740 | |
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| 0.1338 | 1.3205 | 5000 | 0.2526 | 20.7058 | |
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| 0.1434 | 1.5846 | 6000 | 0.2428 | 19.7434 | |
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| 0.1136 | 1.8487 | 7000 | 0.2362 | 19.1380 | |
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| 0.0783 | 2.1128 | 8000 | 0.2387 | 18.7193 | |
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| 0.0692 | 2.3769 | 9000 | 0.2349 | 18.4846 | |
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| 0.0722 | 2.6410 | 10000 | 0.2343 | 18.8605 | |
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| 0.0683 | 2.9051 | 11000 | 0.2297 | 18.0129 | |
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| 0.0482 | 3.1692 | 12000 | 0.2443 | 18.1920 | |
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| 0.0231 | 3.4332 | 13000 | 0.2442 | 17.7089 | |
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| 0.0255 | 3.6973 | 14000 | 0.2468 | 17.7821 | |
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| 0.022 | 3.9614 | 15000 | 0.2455 | 17.5538 | |
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| 0.0092 | 4.2255 | 16000 | 0.2553 | 17.5424 | |
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| 0.0058 | 4.4896 | 17000 | 0.2614 | 17.5828 | |
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| 0.0048 | 4.7537 | 18000 | 0.2593 | 17.2801 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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