readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: xls-r-1b-bemba-10hrs
    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. -->
  
  # xls-r-1b-bemba-10hrs
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2350
  - Wer: 0.3524
  
  ## 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: 3e-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: 400
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.2547        | 0.54  | 400  | 0.4199          | 0.5888 |
  | 0.5422        | 1.07  | 800  | 0.2689          | 0.4360 |
  | 0.4154        | 1.61  | 1200 | 0.2342          | 0.4008 |
  | 0.4075        | 2.15  | 1600 | 0.2172          | 0.3579 |
  | 0.3326        | 2.68  | 2000 | 0.2151          | 0.3603 |
  | 0.2837        | 3.22  | 2400 | 0.2117          | 0.3505 |
  | 0.2688        | 3.76  | 2800 | 0.2040          | 0.3559 |
  | 0.2401        | 4.3   | 3200 | 0.2099          | 0.3445 |
  | 0.2176        | 4.83  | 3600 | 0.1973          | 0.3299 |
  | 0.1913        | 5.37  | 4000 | 0.2123          | 0.3432 |
  | 0.1683        | 5.91  | 4400 | 0.2032          | 0.3358 |
  | 0.1445        | 6.44  | 4800 | 0.2350          | 0.3524 |
  
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  