readme: ---
  license: cc-by-nc-4.0
  tags:
  - generated_from_trainer
  model-index:
  - name: models_sv_eric_1
    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. -->
  
  # models_sv_eric_1
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.1340
  - Wer: 0.6241
  
  ## 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: 0.0001
  - 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: 1000
  - num_epochs: 300
  
  ### Training results
  
  | Training Loss | Epoch  | Step  | Validation Loss | Wer    |
  |:-------------:|:------:|:-----:|:---------------:|:------:|
  | 27.2483       | 5.81   | 250   | 12.8968         | 1.0    |
  | 5.3813        | 11.63  | 500   | 3.7635          | 1.0    |
  | 3.1776        | 17.44  | 750   | 3.1586          | 1.0    |
  | 3.0849        | 23.26  | 1000  | 3.1336          | 1.0    |
  | 3.0351        | 29.07  | 1250  | 3.0069          | 1.0    |
  | 2.5591        | 34.88  | 1500  | 1.8101          | 0.9735 |
  | 1.4236        | 40.7   | 1750  | 1.3666          | 0.8120 |
  | 0.9233        | 46.51  | 2000  | 1.3338          | 0.7470 |
  | 0.6594        | 52.33  | 2250  | 1.4020          | 0.7060 |
  | 0.5056        | 58.14  | 2500  | 1.3793          | 0.7036 |
  | 0.4135        | 63.95  | 2750  | 1.3789          | 0.6988 |
  | 0.3521        | 69.77  | 3000  | 1.4288          | 0.6795 |
  | 0.2728        | 75.58  | 3250  | 1.4819          | 0.6554 |
  | 0.2419        | 81.4   | 3500  | 1.5370          | 0.6602 |
  | 0.2288        | 87.21  | 3750  | 1.4477          | 0.6265 |
  | 0.2009        | 93.02  | 4000  | 1.5387          | 0.6602 |
  | 0.1773        | 98.84  | 4250  | 1.6789          | 0.6723 |
  | 0.1701        | 104.65 | 4500  | 1.6322          | 0.6361 |
  | 0.1562        | 110.47 | 4750  | 1.5988          | 0.6554 |
  | 0.1433        | 116.28 | 5000  | 1.7502          | 0.6458 |
  | 0.1373        | 122.09 | 5250  | 1.7735          | 0.6217 |
  | 0.1186        | 127.91 | 5500  | 1.7193          | 0.6193 |
  | 0.1127        | 133.72 | 5750  | 1.8742          | 0.6410 |
  | 0.113         | 139.53 | 6000  | 1.8339          | 0.6337 |
  | 0.1106        | 145.35 | 6250  | 1.7486          | 0.6289 |
  | 0.0955        | 151.16 | 6500  | 1.7455          | 0.6361 |
  | 0.0934        | 156.98 | 6750  | 1.8922          | 0.6361 |
  | 0.0873        | 162.79 | 7000  | 2.0495          | 0.6530 |
  | 0.0863        | 168.6  | 7250  | 1.8438          | 0.6361 |
  | 0.0901        | 174.42 | 7500  | 2.0441          | 0.6289 |
  | 0.0749        | 180.23 | 7750  | 2.0112          | 0.6265 |
  | 0.0887        | 186.05 | 8000  | 2.0684          | 0.6554 |
  | 0.074         | 191.86 | 8250  | 2.0821          | 0.6265 |
  | 0.0714        | 197.67 | 8500  | 2.0790          | 0.6313 |
  | 0.0638        | 203.49 | 8750  | 2.0158          | 0.6072 |
  | 0.0633        | 209.3  | 9000  | 2.0423          | 0.6386 |
  | 0.0621        | 215.12 | 9250  | 2.0013          | 0.6241 |
  | 0.0616        | 220.93 | 9500  | 1.9567          | 0.6386 |
  | 0.0627        | 226.74 | 9750  | 2.0302          | 0.6361 |
  | 0.0604        | 232.56 | 10000 | 2.0424          | 0.6096 |
  | 0.0551        | 238.37 | 10250 | 2.0238          | 0.6096 |
  | 0.0559        | 244.19 | 10500 | 2.0207          | 0.6361 |
  | 0.0587        | 250.0  | 10750 | 2.0818          | 0.6361 |
  | 0.0508        | 255.81 | 11000 | 2.1106          | 0.6289 |
  | 0.0494        | 261.63 | 11250 | 2.1194          | 0.6434 |
  | 0.0576        | 267.44 | 11500 | 2.0752          | 0.6410 |
  | 0.0521        | 273.26 | 11750 | 2.1455          | 0.6361 |
  | 0.0479        | 279.07 | 12000 | 2.1583          | 0.6337 |
  | 0.0501        | 284.88 | 12250 | 2.1400          | 0.6386 |
  | 0.0447        | 290.7  | 12500 | 2.1440          | 0.6265 |
  | 0.0455        | 296.51 | 12750 | 2.1340          | 0.6241 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.0
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  