84 lines
2.1 KiB
Markdown
84 lines
2.1 KiB
Markdown
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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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base_model: openai/whisper-large-v3
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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 Large TR - \xD6zg\xFCn Tosun"
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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: tr
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split: None
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args: 'config: tr, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 11.727918051936383
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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 Large TR - Özgün Tosun
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) 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: 0.1323
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- Wer: 11.7279
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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: 5000
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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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| 0.1372 | 0.3652 | 1000 | 0.1810 | 16.0805 |
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| 0.1103 | 0.7305 | 2000 | 0.1628 | 14.5458 |
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| 0.0563 | 1.0957 | 3000 | 0.1513 | 12.9302 |
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| 0.0657 | 1.4609 | 4000 | 0.1383 | 12.4198 |
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| 0.0444 | 1.8262 | 5000 | 0.1323 | 11.7279 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.2.2+cu121
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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