readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - bem
  - robust-speech-event
  model-index:
  - name: wav2vec2-large-xls-r-300m-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-300m-bemba-fds
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the [BembaSpeech](https://github.com/csikasote/BembaSpeech) dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3594
  - Wer: 0.3838
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.9961        | 0.67  | 500  | 0.5157          | 0.7133 |
  | 0.5903        | 1.34  | 1000 | 0.3663          | 0.4989 |
  | 0.4804        | 2.02  | 1500 | 0.3547          | 0.4653 |
  | 0.4146        | 2.69  | 2000 | 0.3274          | 0.4345 |
  | 0.3792        | 3.36  | 2500 | 0.3586          | 0.4640 |
  | 0.3509        | 4.03  | 3000 | 0.3360          | 0.4316 |
  | 0.3114        | 4.7   | 3500 | 0.3382          | 0.4303 |
  | 0.2935        | 5.38  | 4000 | 0.3263          | 0.4091 |
  | 0.2723        | 6.05  | 4500 | 0.3348          | 0.4175 |
  | 0.2502        | 6.72  | 5000 | 0.3317          | 0.4147 |
  | 0.2334        | 7.39  | 5500 | 0.3542          | 0.4030 |
  | 0.2287        | 8.06  | 6000 | 0.3594          | 0.4067 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  