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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: NbAiLabBeta/nb-whisper-large
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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-large-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-large-v0.8-vad3-verbatim
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This model is a fine-tuned version of [NbAiLabBeta/nb-whisper-large](https://huggingface.co/NbAiLabBeta/nb-whisper-large) 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: 0.5839
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- train_loss: 0.4632
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- validation_wer: 7.9358
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- validation_cer: 2.5127
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- validation_exact_wer: 8.0494
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- validation_exact_cer: 2.5279
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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: 7e-05
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- lr_scheduler_type: linear
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- per_device_train_batch_size: 8
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- total_train_batch_size_per_node: 32
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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: 32
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- total_num_training_examples: 256,000
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- steps_per_epoch: 97
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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 | 1.2831 | 1.1864 | 18.9083 | 11.8409 | 33.9801 | 15.0322 |
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| 40 | 0.5952 | 0.4958 | 8.9760 | 2.9212 | 9.1099 | 2.9390 |
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| 80 | 0.5848 | 0.4761 | 8.3105 | 2.6432 | 8.4330 | 2.6621 |
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| 120 | 0.5831 | 0.4492 | 8.1204 | 2.5679 | 8.2356 | 2.5821 |
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| 160 | 0.5811 | 0.4678 | 7.9302 | 2.5051 | 8.0438 | 2.5193 |
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| 200 | 0.5840 | 0.4692 | 7.9861 | 2.5346 | 8.0945 | 2.5498 |
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| 240 | 0.5844 | 0.4543 | 7.9246 | 2.5051 | 8.0381 | 2.5193 |
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| 249 | 0.5839 | 0.4632 | 7.9358 | 2.5127 | 8.0494 | 2.5279 |
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### Framework versions
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- Transformers 4.36.2
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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