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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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metrics:
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- wer
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model-index:
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- name: whisper-medium-hi
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results: []
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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-hi
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3957
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- Wer: 0.2425
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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: 16
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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- total_train_batch_size: 32
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- total_eval_batch_size: 32
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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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| 0.0234 | 4.88 | 1000 | 0.2762 | 0.2750 |
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| 0.003 | 9.76 | 2000 | 0.3342 | 0.2518 |
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| 0.0001 | 14.63 | 3000 | 0.3636 | 0.2424 |
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| 0.0 | 19.51 | 4000 | 0.3877 | 0.2426 |
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| 0.0 | 24.39 | 5000 | 0.3957 | 0.2425 |
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### Framework versions
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- Transformers 4.28.0.dev0
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- Pytorch 2.0.0+cu117
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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