readme: ---
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - librispeech_asr
  - generated_from_trainer
  model-index:
  - name: hubert-large-ll60k-librispeech-clean-100h-demo-dist
    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. -->
  
  # hubert-large-ll60k-librispeech-clean-100h-demo-dist
  
  This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the LIBRISPEECH_ASR - CLEAN dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.1361
  - Wer: 0.9769
  
  ## 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: 0.0003
  - train_batch_size: 4
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 3.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.4699        | 0.15  | 100  | 2.0098          | 1.0    |
  | 1.1           | 0.3   | 200  | 1.0910          | 0.9769 |
  | 0.6468        | 0.45  | 300  | 1.5089          | 0.9769 |
  | 0.6928        | 0.61  | 400  | 1.6171          | 1.0    |
  | 0.698         | 0.76  | 500  | 1.2406          | 0.9769 |
  | 1.0461        | 0.91  | 600  | 1.3760          | 1.0    |
  | 0.6363        | 1.06  | 700  | 2.1654          | 1.0    |
  | 0.6743        | 1.21  | 800  | 1.7481          | 0.9769 |
  | 0.565         | 1.36  | 900  | 2.1965          | 1.0    |
  | 0.5761        | 1.51  | 1000 | 1.8223          | 0.9769 |
  | 0.6179        | 1.66  | 1100 | 1.9976          | 0.9769 |
  | 0.5052        | 1.82  | 1200 | 1.5585          | 0.9769 |
  | 0.5434        | 1.97  | 1300 | 2.0349          | 0.9769 |
  | 0.4997        | 2.12  | 1400 | 2.4083          | 0.9769 |
  | 0.489         | 2.27  | 1500 | 2.4164          | 0.9769 |
  | 0.5104        | 2.42  | 1600 | 2.4970          | 0.9769 |
  | 0.5324        | 2.57  | 1700 | 2.3352          | 0.9769 |
  | 0.5207        | 2.72  | 1800 | 2.2009          | 0.9769 |
  | 0.5224        | 2.87  | 1900 | 2.1035          | 0.9769 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0.dev0
  - Pytorch 1.12.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  