readme: 
  
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  # bach-arb
  
  This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-german](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-german) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.9404
  - Wer: 0.6130
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 115
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer    |
  |:-------------:|:------:|:----:|:---------------:|:------:|
  | 27.8653       | 7.14   | 100  | 3.1369          | 1.0    |
  | 2.5975        | 14.28  | 200  | 2.1223          | 0.9976 |
  | 1.2001        | 21.41  | 300  | 1.7455          | 0.8774 |
  | 0.5938        | 28.55  | 400  | 1.8534          | 0.7981 |
  | 0.4001        | 35.69  | 500  | 2.3318          | 0.7740 |
  | 0.2895        | 42.83  | 600  | 2.2214          | 0.7163 |
  | 0.1853        | 49.97  | 700  | 2.4841          | 0.7043 |
  | 0.1318        | 57.14  | 800  | 2.9749          | 0.7139 |
  | 0.1067        | 64.28  | 900  | 2.4759          | 0.7115 |
  | 0.0635        | 71.41  | 1000 | 2.6708          | 0.6635 |
  | 0.0515        | 78.55  | 1100 | 3.0593          | 0.6923 |
  | 0.0455        | 85.69  | 1200 | 2.9637          | 0.6587 |
  | 0.0329        | 92.83  | 1300 | 2.9837          | 0.6346 |
  | 0.0232        | 99.97  | 1400 | 2.9361          | 0.6178 |
  | 0.021         | 107.14 | 1500 | 2.9221          | 0.6010 |
  | 0.0193        | 114.28 | 1600 | 2.9404          | 0.6130 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  