readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-burak-new-300-v2-4
    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. -->
  
  # wav2vec2-burak-new-300-v2-4
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3402
  - Wer: 0.2237
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 131
  
  ### Training results
  
  | Training Loss | Epoch  | Step  | Validation Loss | Wer    |
  |:-------------:|:------:|:-----:|:---------------:|:------:|
  | 7.7711        | 2.45   | 500   | 3.1768          | 1.0    |
  | 3.1194        | 4.9    | 1000  | 2.6401          | 1.0    |
  | 1.4593        | 7.35   | 1500  | 0.5243          | 0.5960 |
  | 0.7581        | 9.8    | 2000  | 0.3534          | 0.4432 |
  | 0.5843        | 12.25  | 2500  | 0.3159          | 0.4157 |
  | 0.4703        | 14.71  | 3000  | 0.3003          | 0.3668 |
  | 0.4045        | 17.16  | 3500  | 0.2891          | 0.3414 |
  | 0.3581        | 19.61  | 4000  | 0.2609          | 0.3207 |
  | 0.3268        | 22.06  | 4500  | 0.2622          | 0.3207 |
  | 0.3063        | 24.51  | 5000  | 0.2805          | 0.3193 |
  | 0.2729        | 26.96  | 5500  | 0.2674          | 0.2884 |
  | 0.249         | 29.41  | 6000  | 0.2740          | 0.2953 |
  | 0.2275        | 31.86  | 6500  | 0.2729          | 0.2753 |
  | 0.2295        | 34.31  | 7000  | 0.2801          | 0.2691 |
  | 0.2105        | 36.76  | 7500  | 0.2992          | 0.2801 |
  | 0.1905        | 39.22  | 8000  | 0.2967          | 0.2663 |
  | 0.1884        | 41.67  | 8500  | 0.2911          | 0.2691 |
  | 0.1773        | 44.12  | 9000  | 0.2966          | 0.2753 |
  | 0.1672        | 46.57  | 9500  | 0.3051          | 0.2505 |
  | 0.1632        | 49.02  | 10000 | 0.2872          | 0.2491 |
  | 0.1553        | 51.47  | 10500 | 0.3121          | 0.2629 |
  | 0.1619        | 53.92  | 11000 | 0.3044          | 0.2581 |
  | 0.1444        | 56.37  | 11500 | 0.3135          | 0.2567 |
  | 0.1451        | 58.82  | 12000 | 0.3033          | 0.2519 |
  | 0.1386        | 61.27  | 12500 | 0.3079          | 0.2622 |
  | 0.1261        | 63.73  | 13000 | 0.3037          | 0.2395 |
  | 0.1287        | 66.18  | 13500 | 0.3221          | 0.2409 |
  | 0.1236        | 68.63  | 14000 | 0.3179          | 0.2464 |
  | 0.1215        | 71.08  | 14500 | 0.3521          | 0.2429 |
  | 0.1208        | 73.53  | 15000 | 0.3481          | 0.2540 |
  | 0.1128        | 75.98  | 15500 | 0.3288          | 0.2402 |
  | 0.1108        | 78.43  | 16000 | 0.3238          | 0.2450 |
  | 0.1074        | 80.88  | 16500 | 0.3178          | 0.2416 |
  | 0.1086        | 83.33  | 17000 | 0.3461          | 0.2361 |
  | 0.1059        | 85.78  | 17500 | 0.3342          | 0.2457 |
  | 0.0981        | 88.24  | 18000 | 0.3382          | 0.2354 |
  | 0.0995        | 90.69  | 18500 | 0.3466          | 0.2416 |
  | 0.0995        | 93.14  | 19000 | 0.3326          | 0.2271 |
  | 0.0929        | 95.59  | 19500 | 0.3526          | 0.2237 |
  | 0.0944        | 98.04  | 20000 | 0.3516          | 0.2347 |
  | 0.089         | 100.49 | 20500 | 0.3504          | 0.2271 |
  | 0.0915        | 102.94 | 21000 | 0.3425          | 0.2285 |
  | 0.0845        | 105.39 | 21500 | 0.3309          | 0.2306 |
  | 0.0887        | 107.84 | 22000 | 0.3196          | 0.2264 |
  | 0.0812        | 110.29 | 22500 | 0.3285          | 0.2264 |
  | 0.0856        | 112.75 | 23000 | 0.3347          | 0.2251 |
  | 0.0778        | 115.2  | 23500 | 0.3403          | 0.2271 |
  | 0.0748        | 117.65 | 24000 | 0.3427          | 0.2278 |
  | 0.0803        | 120.1  | 24500 | 0.3380          | 0.2223 |
  | 0.0768        | 122.55 | 25000 | 0.3392          | 0.2189 |
  | 0.0764        | 125.0  | 25500 | 0.3423          | 0.2278 |
  | 0.0786        | 127.45 | 26000 | 0.3423          | 0.2230 |
  | 0.0766        | 129.9  | 26500 | 0.3402          | 0.2237 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  