readme: ---
  language:
  - en_us
  license: apache-2.0
  tags:
  - fleurs-asr
  - google/xtreme_s
  - generated_from_trainer
  datasets:
  - google/xtreme_s
  model-index:
  - name: xtreme_s_xlsr_300m_fleurs_asr_en_us
    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. -->
  
  # xtreme_s_xlsr_300m_fleurs_asr_en_us
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the GOOGLE/XTREME_S - FLEURS.EN_US dataset.
  It achieves the following results on the evaluation set:
  - Cer: 0.1356
  - Loss: 0.5599
  - Wer: 0.3148
  - Predict Samples: 647
  
  ## 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: 1
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 8
  - total_train_batch_size: 64
  - total_eval_batch_size: 8
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 200
  - num_epochs: 30.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
  | 2.8769        | 5.0   | 200  | 2.8871          | 1.0    | 0.9878 |
  | 0.2458        | 10.0  | 400  | 0.5570          | 0.4899 | 0.1951 |
  | 0.0762        | 15.0  | 600  | 0.5213          | 0.3727 | 0.1562 |
  | 0.0334        | 20.0  | 800  | 0.5742          | 0.3666 | 0.1543 |
  | 0.0244        | 25.0  | 1000 | 0.5907          | 0.3546 | 0.1499 |
  | 0.0143        | 30.0  | 1200 | 0.5961          | 0.3460 | 0.1469 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0.dev0
  - Pytorch 1.10.1+cu111
  - Datasets 1.18.4.dev0
  - Tokenizers 0.11.6
  