readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - bem
  - robust-speech-event
  model-index:
  - name: wav2vec2-large-xls-r-1b-bemba-fds
    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. -->
  
  # wav2vec2-large-xls-r-1b-bemba-fds
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the [BembaSpeech](https://github.com/csikasote/BembaSpeech) dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2898
  - Wer: 0.3435
  
  ## 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: 5e-05
  - train_batch_size: 4
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 8
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 15
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.7986        | 0.34  | 500  | 0.4549          | 0.7292 |
  | 0.5358        | 0.67  | 1000 | 0.3325          | 0.4491 |
  | 0.4559        | 1.01  | 1500 | 0.3090          | 0.3954 |
  | 0.3983        | 1.35  | 2000 | 0.3067          | 0.4105 |
  | 0.4067        | 1.68  | 2500 | 0.2838          | 0.3678 |
  | 0.3722        | 2.02  | 3000 | 0.2824          | 0.3762 |
  | 0.3286        | 2.36  | 3500 | 0.2810          | 0.3670 |
  | 0.3239        | 2.69  | 4000 | 0.2643          | 0.3501 |
  | 0.3187        | 3.03  | 4500 | 0.2838          | 0.3754 |
  | 0.2801        | 3.36  | 5000 | 0.2815          | 0.3507 |
  | 0.2806        | 3.7   | 5500 | 0.2725          | 0.3486 |
  | 0.2714        | 4.04  | 6000 | 0.2898          | 0.3435 |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  