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stats.md
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---
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language:
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- 'no'
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license: apache-2.0
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base_model: NbAiLab/nb-whisper-medium-v0.8-vad3
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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: nb-whisper-medium-v0.8-vad3-verbatim
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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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# nb-whisper-medium-v0.8-vad3-verbatim
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This model is a fine-tuned version of [NbAiLab/nb-whisper-medium-v0.8-vad3](https://huggingface.co/NbAiLab/nb-whisper-medium-v0.8-vad3) on the NbAiLab/NPSC dataset.
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It achieves the following results on the evaluation set:
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- step: 249
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- validation_loss: 0.6296
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- train_loss: 0.4324
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- validation_wer: 8.2769
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- validation_cer: 2.8193
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- validation_exact_wer: 8.4048
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- validation_exact_cer: 2.8363
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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: 2.5e-05
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- lr_scheduler_type: linear
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- per_device_train_batch_size: 32
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- total_train_batch_size_per_node: 128
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- total_train_batch_size: 1024
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- total_optimization_steps: 250
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- starting_optimization_step: None
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- finishing_optimization_step: 250
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- num_train_dataset_workers: 32
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- num_hosts: 8
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- total_num_training_examples: 256,000
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- steps_per_epoch: 45
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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 | 1.5895 | 1.4606 | 17.5605 | 10.5650 | 33.0099 | 13.8415 |
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| 40 | 0.6409 | 0.5035 | 9.1662 | 3.0250 | 9.3637 | 3.0542 |
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| 80 | 0.6309 | 0.4790 | 8.7132 | 2.9755 | 8.8730 | 2.9952 |
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| 120 | 0.6250 | 0.4480 | 8.4503 | 2.8812 | 8.6079 | 2.9019 |
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| 160 | 0.6294 | 0.4423 | 8.4000 | 2.8641 | 8.5345 | 2.8810 |
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| 200 | 0.6276 | 0.4467 | 8.3161 | 2.8345 | 8.4668 | 2.8534 |
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| 240 | 0.6287 | 0.4376 | 8.2266 | 2.7917 | 8.3597 | 2.8087 |
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| 249 | 0.6296 | 0.4324 | 8.2769 | 2.8193 | 8.4048 | 2.8363 |
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### Framework versions
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- Transformers 4.34.1
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- Datasets 2.16.1
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- Tokenizers 0.14.1
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