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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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base_model: openai/whisper-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- Jzuluaga/atcosim_corpus |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper small - Whisper with atcosim |
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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: 'This is a dataset constructed from two datasets: ATCO2-ASR and ATCOSIM.' |
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type: Jzuluaga/atcosim_corpus |
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args: 'config: en, split: test small split [3000]' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 8.947972793922798 |
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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 - Whisper with atcosim |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the This is a dataset constructed from two datasets: ATCO2-ASR and ATCOSIM. dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2504 |
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- Wer: 8.9480 |
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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: 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: 50 |
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- training_steps: 1000 |
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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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| 0.0569 | 0.5319 | 100 | 0.3078 | 11.7922 | |
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| 0.0307 | 1.0638 | 200 | 0.2728 | 10.8515 | |
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| 0.0253 | 1.5957 | 300 | 0.2762 | 10.7190 | |
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| 0.0066 | 2.1277 | 400 | 0.2551 | 9.0761 | |
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| 0.0061 | 2.6596 | 500 | 0.2526 | 9.5795 | |
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| 0.002 | 3.1915 | 600 | 0.2504 | 9.0010 | |
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| 0.0019 | 3.7234 | 700 | 0.2561 | 9.2880 | |
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| 0.0007 | 4.2553 | 800 | 0.2535 | 9.1026 | |
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| 0.001 | 4.7872 | 900 | 0.2495 | 8.9259 | |
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| 0.0003 | 5.3191 | 1000 | 0.2504 | 8.9480 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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