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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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- audiofolder
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metrics:
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- wer
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model-index:
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- name: whisper-medium-ar-original
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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: audiofolder
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type: audiofolder
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config: default
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split: train
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args: default
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metrics:
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- name: Wer
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type: wer
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value: 14.108618654073199
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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-ar-original
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the audiofolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1852
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- Wer: 14.1086
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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: 24
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- eval_batch_size: 24
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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: 8000
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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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| 0.115 | 1.01 | 400 | 0.1204 | 18.6541 |
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| 0.0774 | 2.02 | 800 | 0.1074 | 15.5844 |
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| 0.0438 | 3.03 | 1200 | 0.1160 | 16.4699 |
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| 0.0233 | 4.04 | 1600 | 0.1279 | 15.1122 |
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| 0.0131 | 5.05 | 2000 | 0.1350 | 15.5254 |
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| 0.0051 | 6.06 | 2400 | 0.1455 | 14.9941 |
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| 0.0035 | 7.07 | 2800 | 0.1464 | 14.1677 |
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| 0.0032 | 8.08 | 3200 | 0.1545 | 14.8170 |
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| 0.0013 | 9.09 | 3600 | 0.1623 | 13.8725 |
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| 0.0013 | 10.1 | 4000 | 0.1543 | 13.4002 |
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| 0.0006 | 11.11 | 4400 | 0.1653 | 14.1677 |
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| 0.0006 | 12.12 | 4800 | 0.1699 | 13.7544 |
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| 0.0003 | 13.13 | 5200 | 0.1705 | 13.4593 |
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| 0.0001 | 14.14 | 5600 | 0.1733 | 13.6954 |
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| 0.0002 | 15.15 | 6000 | 0.1768 | 13.8725 |
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| 0.0001 | 16.16 | 6400 | 0.1786 | 13.7544 |
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| 0.0 | 17.17 | 6800 | 0.1826 | 13.9906 |
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| 0.0 | 18.18 | 7200 | 0.1839 | 14.0496 |
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| 0.0 | 19.19 | 7600 | 0.1848 | 14.0496 |
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| 0.0 | 20.2 | 8000 | 0.1852 | 14.1086 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.12.1
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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