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_w2v2_minds14.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_w2v2_minds14.en-US
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) on the GOOGLE/XTREME_S - MINDS14.EN-US dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5337
  - F1: 0.9144
  - Accuracy: 0.9113
  
  ## 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: 150.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | F1     | Accuracy |
  |:-------------:|:------:|:----:|:---------------:|:------:|:--------:|
  | 2.6482        | 3.95   | 20   | 2.6421          | 0.0242 | 0.0745   |
  | 2.6292        | 7.95   | 40   | 2.6359          | 0.0108 | 0.0816   |
  | 2.5993        | 11.95  | 60   | 2.6301          | 0.0167 | 0.0674   |
  | 2.4023        | 15.95  | 80   | 2.5514          | 0.1105 | 0.1454   |
  | 1.4015        | 19.95  | 100  | 1.6843          | 0.5599 | 0.5851   |
  | 0.4379        | 23.95  | 120  | 0.8126          | 0.7921 | 0.7908   |
  | 0.0642        | 27.95  | 140  | 0.7178          | 0.8158 | 0.8156   |
  | 0.0376        | 31.95  | 160  | 0.7286          | 0.8473 | 0.8475   |
  | 0.0185        | 35.95  | 180  | 0.6779          | 0.8719 | 0.8723   |
  | 0.0752        | 39.95  | 200  | 0.7096          | 0.8578 | 0.8511   |
  | 0.0266        | 43.95  | 220  | 0.7655          | 0.8596 | 0.8546   |
  | 0.0078        | 47.95  | 240  | 0.7623          | 0.8563 | 0.8511   |
  | 0.007         | 51.95  | 260  | 0.6620          | 0.8794 | 0.8759   |
  | 0.0047        | 55.95  | 280  | 0.5936          | 0.9045 | 0.9007   |
  | 0.0067        | 59.95  | 300  | 0.8279          | 0.8546 | 0.8617   |
  | 0.0394        | 63.95  | 320  | 0.8766          | 0.8359 | 0.8227   |
  | 0.0051        | 67.95  | 340  | 0.8097          | 0.8483 | 0.8475   |
  | 0.0095        | 71.95  | 360  | 0.6095          | 0.9083 | 0.9078   |
  | 0.0026        | 75.95  | 380  | 0.5286          | 0.8889 | 0.8865   |
  | 0.0023        | 79.95  | 400  | 0.7218          | 0.8926 | 0.8936   |
  | 0.0023        | 83.95  | 420  | 0.6551          | 0.8997 | 0.8972   |
  | 0.0027        | 87.95  | 440  | 0.6664          | 0.8848 | 0.8794   |
  | 0.0019        | 91.95  | 460  | 0.5344          | 0.9032 | 0.9043   |
  | 0.002         | 95.95  | 480  | 0.5863          | 0.8983 | 0.9007   |
  | 0.0015        | 99.95  | 500  | 0.5715          | 0.9047 | 0.9043   |
  | 0.0016        | 103.95 | 520  | 0.5615          | 0.8956 | 0.8936   |
  | 0.0014        | 107.95 | 540  | 0.6353          | 0.8965 | 0.8936   |
  | 0.0014        | 111.95 | 560  | 0.5593          | 0.9041 | 0.9007   |
  | 0.0013        | 115.95 | 580  | 0.6041          | 0.8977 | 0.8936   |
  | 0.0013        | 119.95 | 600  | 0.5794          | 0.9026 | 0.9007   |
  | 0.0012        | 123.95 | 620  | 0.6858          | 0.9003 | 0.8972   |
  | 0.0013        | 127.95 | 640  | 0.6730          | 0.9002 | 0.8972   |
  | 0.0013        | 131.95 | 660  | 0.5707          | 0.9146 | 0.9113   |
  | 0.0012        | 135.95 | 680  | 0.5604          | 0.9153 | 0.9113   |
  | 0.0019        | 139.95 | 700  | 0.5468          | 0.9114 | 0.9078   |
  | 0.0015        | 143.95 | 720  | 0.5361          | 0.9144 | 0.9113   |
  | 0.0012        | 147.95 | 740  | 0.5337          | 0.9144 | 0.9113   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  