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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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base_model: openai/whisper-small |
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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 Base ATCOSIM |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: atcosim_corpus_numbers_converted |
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type: Jzuluaga/atcosim_corpus |
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args: 'config: en, split: test' |
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metrics: |
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- type: wer |
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value: 8.400080770007404 |
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name: Wer |
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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 Base ATCOSIM |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the atcosim_corpus_numbers_converted dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0493 |
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- Wer: 8.4001 |
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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: 500 |
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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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| 1.5879 | 0.2092 | 100 | 1.3381 | 79.2825 | |
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| 0.6066 | 0.4184 | 200 | 0.5917 | 21.4916 | |
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| 0.1067 | 0.6276 | 300 | 0.1257 | 15.2319 | |
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| 0.0632 | 0.8368 | 400 | 0.0855 | 15.0973 | |
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| 0.0366 | 1.0460 | 500 | 0.0768 | 11.7655 | |
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| 0.0184 | 1.2552 | 600 | 0.0685 | 15.9992 | |
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| 0.0345 | 1.4644 | 700 | 0.0629 | 9.5578 | |
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| 0.0279 | 1.6736 | 800 | 0.0543 | 9.8607 | |
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| 0.0186 | 1.8828 | 900 | 0.0499 | 9.6655 | |
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| 0.0067 | 2.0921 | 1000 | 0.0493 | 8.4001 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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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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