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End of training

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  1. README.md +86 -0
  2. generation_config.json +256 -0
README.md ADDED
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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 Base 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: atcosim_corpus
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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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+ - name: Wer
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+ type: wer
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+ value: 4.169242999735006
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+ ---
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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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+
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+ # Whisper Base ATCOSIM
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+
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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 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0557
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+ - Wer: 4.1692
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:------:|:----:|:---------------:|:-------:|
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+ | 1.6572 | 0.2092 | 100 | 1.2694 | 71.0096 |
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+ | 0.3373 | 0.4184 | 200 | 0.3225 | 16.4296 |
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+ | 0.147 | 0.6276 | 300 | 0.1653 | 9.2130 |
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+ | 0.0975 | 0.8368 | 400 | 0.1107 | 6.3334 |
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+ | 0.0544 | 1.0460 | 500 | 0.0892 | 6.2583 |
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+ | 0.0344 | 1.2552 | 600 | 0.0760 | 5.4103 |
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+ | 0.0517 | 1.4644 | 700 | 0.0663 | 5.0393 |
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+ | 0.0396 | 1.6736 | 800 | 0.0607 | 4.3106 |
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+ | 0.0297 | 1.8828 | 900 | 0.0566 | 4.2708 |
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+ | 0.0133 | 2.0921 | 1000 | 0.0557 | 4.1692 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.0.dev0
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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