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update model card README.md
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README.md
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---
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language:
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- en
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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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- luigisaetta/atco2_normalized_augmented
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metrics:
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- wer
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model-index:
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- name: whisper-atco2-medium
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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: luigisaetta/atco2_normalized_augmented
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type: luigisaetta/atco2_normalized_augmented
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config: null
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split: None
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metrics:
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- name: Wer
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type: wer
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value: 17.50524109014675
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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-atco2-medium
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the luigisaetta/atco2_normalized_augmented dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6129
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- Wer: 17.5052
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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: 2
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_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: 200
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- training_steps: 500
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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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| 2.3939 | 1.06 | 50 | 1.8493 | 66.5618 |
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| 0.5127 | 2.13 | 100 | 0.5119 | 30.6080 |
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| 0.0626 | 3.19 | 150 | 0.5410 | 20.4403 |
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| 0.0157 | 4.25 | 200 | 0.5775 | 19.8113 |
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| 0.0107 | 5.32 | 250 | 0.5552 | 19.7065 |
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| 0.0044 | 6.38 | 300 | 0.5723 | 18.1342 |
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| 0.0013 | 7.45 | 350 | 0.5763 | 17.7149 |
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| 0.0005 | 8.51 | 400 | 0.6053 | 17.7149 |
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| 0.0004 | 9.57 | 450 | 0.6109 | 17.5052 |
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| 0.0004 | 10.64 | 500 | 0.6129 | 17.5052 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.0+cu117
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- Datasets 2.7.1.dev0
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- Tokenizers 0.11.0
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