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README.md
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---
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language:
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- hy
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license: apache-2.0
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tags:
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- whisper-event
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_11_0
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- google/fleurs
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metrics:
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- wer
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model-index:
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- name: whisper-base-hy
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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 11.0
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type: mozilla-foundation/common_voice_11_0
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config: hy-AM
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split: test
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args: hy-AM
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metrics:
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- name: Wer
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type: wer
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value: 22.36842105263158
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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-base-hy
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 11.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2204
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- Wer: 22.3684
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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: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 64
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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: 200
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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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| 0.1394 | 5.87 | 400 | 0.1780 | 28.2895 |
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| 0.0536 | 11.75 | 800 | 0.1739 | 24.6053 |
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| 0.0247 | 17.64 | 1200 | 0.2098 | 22.9605 |
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| 0.0154 | 23.52 | 1600 | 0.2035 | 22.1382 |
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| 0.0103 | 29.41 | 2000 | 0.2204 | 22.3684 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.0+cu117
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- Datasets 2.7.1.dev0
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- Tokenizers 0.13.2
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