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update model card README.md
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README.md
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---
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_11_0
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metrics:
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- wer
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model-index:
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- name: whisper-el-medium-augmented-1
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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: common_voice_11_0
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config: el
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split: test
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args: el
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metrics:
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- name: Wer
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type: wer
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value: 24.322065378900444
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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-el-medium-augmented-1
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This model was trained from scratch 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: 0.4328
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- Wer: 24.3221
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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-05
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- train_batch_size: 8
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- eval_batch_size: 4
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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: 10000
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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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| 0.0905 | 2.35 | 1000 | 0.5419 | 37.8343 |
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| 0.0552 | 4.69 | 2000 | 0.5118 | 34.6954 |
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| 0.0329 | 7.04 | 3000 | 0.5332 | 32.3180 |
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| 0.0219 | 9.39 | 4000 | 0.5185 | 30.1913 |
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| 0.0161 | 11.74 | 5000 | 0.4908 | 32.3366 |
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| 0.0063 | 14.08 | 6000 | 0.4741 | 28.4733 |
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| 0.0015 | 16.43 | 7000 | 0.4400 | 26.3187 |
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| 0.001 | 18.78 | 8000 | 0.4428 | 25.5293 |
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| 0.0001 | 21.13 | 9000 | 0.4382 | 25.2043 |
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| 0.0014 | 23.47 | 10000 | 0.4328 | 24.3221 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.11.0+cu113
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- Datasets 2.7.1
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- Tokenizers 0.12.1
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