readme: ---
  language:
  - en-US
  license: apache-2.0
  tags:
  - minds14
  - google/xtreme_s
  - generated_from_trainer
  datasets:
  - xtreme_s
  metrics:
  - f1
  - accuracy
  model-index:
  - name: xtreme_s_xlsr_300m_minds14.en-US_2
    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_minds14.en-US_2
  
  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 - MINDS14.EN-US dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5685
  - F1: 0.8747
  - Accuracy: 0.8759
  
  ## 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: 2
  - eval_batch_size: 8
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 2
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 32
  - total_eval_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 100
  - num_epochs: 50.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
  | 2.6195        | 3.95  | 20   | 2.6348          | 0.0172 | 0.0816   |
  | 2.5925        | 7.95  | 40   | 2.6119          | 0.0352 | 0.0851   |
  | 2.1271        | 11.95 | 60   | 2.3066          | 0.1556 | 0.1986   |
  | 1.2618        | 15.95 | 80   | 1.3810          | 0.6877 | 0.7128   |
  | 0.5455        | 19.95 | 100  | 1.0403          | 0.6992 | 0.7270   |
  | 0.2571        | 23.95 | 120  | 0.8423          | 0.8160 | 0.8121   |
  | 0.3478        | 27.95 | 140  | 0.6500          | 0.8516 | 0.8440   |
  | 0.0732        | 31.95 | 160  | 0.7066          | 0.8123 | 0.8156   |
  | 0.1092        | 35.95 | 180  | 0.5878          | 0.8767 | 0.8759   |
  | 0.0271        | 39.95 | 200  | 0.5994          | 0.8578 | 0.8617   |
  | 0.4664        | 43.95 | 220  | 0.7830          | 0.8403 | 0.8440   |
  | 0.0192        | 47.95 | 240  | 0.5685          | 0.8747 | 0.8759   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  