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language: |
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- et |
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license: apache-2.0 |
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base_model: openai/whisper-large-v2 |
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tags: |
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- audio |
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- asr |
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- automatic-speech-recognition |
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- hf-asr-leaderboard |
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model-index: |
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- name: salmon-whisper-large-smj-lr5e-5 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# salmon-whisper-large-smj-lr5e-5 |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the NbAiLab/salmon-asr-smj dataset. |
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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: 5e-05 |
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- lr_scheduler_type: linear |
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- per_device_train_batch_size: 6 |
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- total_train_batch_size_per_node: 48 |
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- total_train_batch_size: 48 |
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- total_optimization_steps: 100,000 |
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- starting_optimization_step: None |
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- finishing_optimization_step: 100,000 |
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- num_train_dataset_workers: 32 |
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- num_hosts: 1 |
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- total_num_training_examples: 4,800,000 |
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- steps_per_epoch: 385 |
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- num_beams: None |
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- weight_decay: 0.01 |
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- adam_beta1: 0.9 |
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- adam_beta2: 0.98 |
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- adam_epsilon: 1e-06 |
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- dropout: True |
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- bpe_dropout_probability: 0.2 |
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- activation_dropout_probability: 0.1 |
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### Training results |
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| step | validation_loss | train_loss | validation_wer | validation_cer | validation_exact_wer | validation_exact_cer | |
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|:-----:|:---------------:|:----------:|:--------------:|:--------------:|:--------------------:|:--------------------:| |
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| 0 | 4.2254 | 4.6413 | 112.7660 | 59.8700 | 108.1117 | 62.0594 | |
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| 10000 | 0.8720 | 0.3747 | 18.2181 | 5.2803 | 21.4096 | 5.6762 | |
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| 20000 | 1.1365 | 0.2741 | 15.2926 | 4.6304 | 18.0851 | 5.0588 | |
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| 30000 | 1.2561 | 0.2111 | 14.6277 | 4.0617 | 17.9521 | 4.5011 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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