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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: emilios/whisper-sm-el-farsipal-e4
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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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# emilios/whisper-sm-el-farsipal-e4
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This model is a fine-tuned version of [emilios/whisper-sm-el-farsipal-e4](https://huggingface.co/emilios/whisper-sm-el-farsipal-e4) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4968
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- Wer: 17.8306
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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: 32
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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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- 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: 20000
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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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| 0.1259 | 2.49 | 1000 | 0.4834 | 18.3692 |
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| 0.1002 | 4.49 | 2000 | 0.4604 | 17.8027 |
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| 0.1096 | 6.98 | 3000 | 0.4553 | 17.8770 |
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| 0.0885 | 9.46 | 4000 | 0.4551 | 17.9606 |
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| 0.0675 | 11.95 | 5000 | 0.4631 | 17.9049 |
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| 0.0675 | 14.44 | 6000 | 0.4619 | 17.9049 |
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| 0.0645 | 16.93 | 7000 | 0.4678 | 17.6727 |
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| 0.0535 | 19.41 | 8000 | 0.4685 | 17.6634 |
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| 0.039 | 21.49 | 9000 | 0.4746 | 17.6727 |
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| 0.0447 | 23.98 | 10000 | 0.4761 | 17.6634 |
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| 0.0393 | 26.46 | 11000 | 0.4792 | 17.7656 |
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| 0.0308 | 28.95 | 12000 | 0.4851 | 17.8678 |
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| 0.0301 | 31.44 | 13000 | 0.4846 | 17.4499 |
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| 0.031 | 33.93 | 14000 | 0.4849 | 17.8306 |
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| 0.0263 | 36.41 | 15000 | 0.4880 | 17.6170 |
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| 0.0256 | 38.9 | 16000 | 0.4871 | 17.1991 |
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| 0.0236 | 41.39 | 17000 | 0.4883 | 17.2641 |
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| 0.0195 | 43.88 | 18000 | 0.4880 | 17.5706 |
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| 0.0193 | 46.36 | 19000 | 0.4993 | 17.7285 |
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| 0.0161 | 48.85 | 20000 | 0.4968 | 17.8306 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 2.0.0.dev20221216+cu116
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- Datasets 2.7.1.dev0
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- Tokenizers 0.13.2
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