readme: ---
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - automatic-speech-recognition
  - NbAiLab/NST
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: whisper-medium-NST-uf-linlr
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # whisper-medium-NST-uf-linlr
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the NBAILAB/NST - NO-CLOSE dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3007
  - Wer: 9.1220
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 1e-05
  - train_batch_size: 72
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - training_steps: 20000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.2046        | 0.05  | 1000  | 0.3426          | 15.2794 |
  | 0.148         | 0.1   | 2000  | 0.3284          | 10.8324 |
  | 0.121         | 0.15  | 3000  | 0.3092          | 12.8848 |
  | 0.1089        | 0.2   | 4000  | 0.2808          | 10.4903 |
  | 0.0976        | 0.25  | 5000  | 0.2617          | 9.9202  |
  | 0.0901        | 0.3   | 6000  | 0.2604          | 21.8928 |
  | 0.0834        | 0.35  | 7000  | 0.2877          | 9.3501  |
  | 0.0825        | 0.4   | 8000  | 0.2794          | 9.3501  |
  | 0.0553        | 1.05  | 9000  | 0.2845          | 9.5781  |
  | 0.0472        | 1.1   | 10000 | 0.2814          | 24.1733 |
  | 0.0409        | 1.15  | 11000 | 0.3084          | 8.0958  |
  | 0.041         | 1.2   | 12000 | 0.2865          | 9.2360  |
  | 0.0353        | 1.25  | 13000 | 0.2828          | 6.4994  |
  | 0.0348        | 1.3   | 14000 | 0.2708          | 7.5257  |
  | 0.0349        | 1.35  | 15000 | 0.2842          | 23.0331 |
  | 0.0361        | 1.4   | 16000 | 0.2769          | 10.1482 |
  | 0.0249        | 2.04  | 17000 | 0.2935          | 8.8940  |
  | 0.0204        | 2.09  | 18000 | 0.2874          | 12.4287 |
  | 0.0175        | 2.14  | 19000 | 0.2882          | 12.9989 |
  | 0.0197        | 2.19  | 20000 | 0.3007          | 9.1220  |
  
  
  ### Framework versions
  
  - Transformers 4.25.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  