readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: model_en
    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. -->
  
  # model_en
  
  This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8610
  - Wer: 0.2641
  
  ## 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: 200
  
  ### Training results
  
  | Training Loss | Epoch  | Step  | Validation Loss | Wer    |
  |:-------------:|:------:|:-----:|:---------------:|:------:|
  | 6.3443        | 3.05   | 250   | 3.0966          | 1.0    |
  | 2.9847        | 6.1    | 500   | 3.0603          | 1.0    |
  | 2.9263        | 9.15   | 750   | 2.9131          | 1.0    |
  | 2.2584        | 12.19  | 1000  | 1.4318          | 0.6575 |
  | 1.2603        | 15.24  | 1250  | 1.1964          | 0.4994 |
  | 0.9182        | 18.29  | 1500  | 1.1494          | 0.4485 |
  | 0.7462        | 21.34  | 1750  | 1.2171          | 0.4357 |
  | 0.6129        | 24.39  | 2000  | 1.0557          | 0.3468 |
  | 0.5364        | 27.44  | 2250  | 1.1069          | 0.4222 |
  | 0.4607        | 30.48  | 2500  | 1.3270          | 0.3370 |
  | 0.4139        | 33.53  | 2750  | 1.1814          | 0.3658 |
  | 0.3587        | 36.58  | 3000  | 1.2423          | 0.3419 |
  | 0.321         | 39.63  | 3250  | 1.2931          | 0.3211 |
  | 0.2961        | 42.68  | 3500  | 1.1409          | 0.3315 |
  | 0.2635        | 45.73  | 3750  | 1.4537          | 0.3241 |
  | 0.2498        | 48.78  | 4000  | 1.2643          | 0.3192 |
  | 0.2352        | 51.82  | 4250  | 1.2789          | 0.3278 |
  | 0.2193        | 54.87  | 4500  | 1.4220          | 0.3021 |
  | 0.2068        | 57.92  | 4750  | 1.3567          | 0.3713 |
  | 0.2055        | 60.97  | 5000  | 1.5375          | 0.3051 |
  | 0.198         | 64.02  | 5250  | 1.2676          | 0.2782 |
  | 0.1835        | 67.07  | 5500  | 1.3905          | 0.2825 |
  | 0.1655        | 70.12  | 5750  | 1.7000          | 0.2978 |
  | 0.1677        | 73.17  | 6000  | 1.4250          | 0.2812 |
  | 0.1522        | 76.22  | 6250  | 1.4220          | 0.2941 |
  | 0.1522        | 79.27  | 6500  | 1.5195          | 0.3021 |
  | 0.1344        | 82.32  | 6750  | 1.3749          | 0.2996 |
  | 0.1298        | 85.36  | 7000  | 1.6663          | 0.2849 |
  | 0.1293        | 88.41  | 7250  | 1.4564          | 0.2892 |
  | 0.1264        | 91.46  | 7500  | 1.4373          | 0.2935 |
  | 0.1243        | 94.51  | 7750  | 1.6572          | 0.2972 |
  | 0.1141        | 97.56  | 8000  | 1.4936          | 0.2892 |
  | 0.1086        | 100.61 | 8250  | 1.5231          | 0.2868 |
  | 0.1056        | 103.65 | 8500  | 1.3733          | 0.2763 |
  | 0.098         | 106.7  | 8750  | 1.4887          | 0.2923 |
  | 0.0984        | 109.75 | 9000  | 1.3779          | 0.2923 |
  | 0.0916        | 112.8  | 9250  | 1.4868          | 0.2604 |
  | 0.0881        | 115.85 | 9500  | 1.7991          | 0.2996 |
  | 0.0846        | 118.9  | 9750  | 1.5845          | 0.2849 |
  | 0.0861        | 121.95 | 10000 | 1.6684          | 0.2794 |
  | 0.0806        | 124.99 | 10250 | 1.5774          | 0.3039 |
  | 0.0822        | 128.05 | 10500 | 1.5928          | 0.2886 |
  | 0.0788        | 131.1  | 10750 | 1.6158          | 0.2880 |
  | 0.0704        | 134.15 | 11000 | 1.7679          | 0.2941 |
  | 0.0721        | 137.19 | 11250 | 1.7055          | 0.2629 |
  | 0.0723        | 140.24 | 11500 | 1.5473          | 0.2653 |
  | 0.0676        | 143.29 | 11750 | 1.8963          | 0.2745 |
  | 0.0665        | 146.34 | 12000 | 1.6367          | 0.2739 |
  | 0.0618        | 149.39 | 12250 | 1.6757          | 0.2745 |
  | 0.0595        | 152.44 | 12500 | 1.5900          | 0.2745 |
  | 0.056         | 155.48 | 12750 | 1.5362          | 0.2794 |
  | 0.0587        | 158.53 | 13000 | 1.4616          | 0.2684 |
  | 0.0519        | 161.58 | 13250 | 1.6867          | 0.2549 |
  | 0.0569        | 164.63 | 13500 | 1.8294          | 0.2574 |
  | 0.0497        | 167.68 | 13750 | 1.7844          | 0.2868 |
  | 0.0531        | 170.73 | 14000 | 1.7564          | 0.2770 |
  | 0.0489        | 173.78 | 14250 | 1.5811          | 0.2629 |
  | 0.0524        | 176.82 | 14500 | 1.6925          | 0.2684 |
  | 0.0431        | 179.87 | 14750 | 1.7236          | 0.2653 |
  | 0.0457        | 182.92 | 15000 | 1.7460          | 0.2512 |
  | 0.045         | 185.97 | 15250 | 1.8096          | 0.2610