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update model card README.md
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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- afrispeech-200
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metrics:
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- wer
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model-index:
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- name: whisper-small-hi-2400_500_100
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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: afrispeech-200
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type: afrispeech-200
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config: all
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split: train
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args: all
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metrics:
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- name: Wer
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type: wer
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value: 0.6376484560570072
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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-hi-2400_500_100
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the afrispeech-200 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1136
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- Wer: 0.6376
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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-06
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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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- 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: 900
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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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| 2.0658 | 0.17 | 150 | 2.3108 | 1.0536 |
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| 1.4738 | 0.33 | 300 | 1.3138 | 1.0395 |
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| 0.8823 | 1.17 | 450 | 1.2148 | 0.7992 |
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| 1.1971 | 1.33 | 600 | 1.1466 | 0.7340 |
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| 0.7529 | 2.17 | 750 | 1.1256 | 0.6723 |
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| 1.1194 | 2.33 | 900 | 1.1136 | 0.6376 |
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### Framework versions
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- Transformers 4.28.0.dev0
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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