readme: 
  
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  # d-l-dl
  
  This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.4495
  - Wer: 1.0
  
  ## 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: 800
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer |
  |:-------------:|:-----:|:----:|:---------------:|:---:|
  | 42.4143       | 49.8  | 100  | 21.5116         | 1.0 |
  | 5.9884        | 99.8  | 200  | 31.7976         | 1.0 |
  | 4.0043        | 149.8 | 300  | 3.4829          | 1.0 |
  | 3.653         | 199.8 | 400  | 3.6417          | 1.0 |
  | 3.5207        | 249.8 | 500  | 3.5081          | 1.0 |
  | 3.63          | 299.8 | 600  | 3.4836          | 1.0 |
  | 3.648         | 349.8 | 700  | 3.4515          | 1.0 |
  | 3.6448        | 399.8 | 800  | 3.4647          | 1.0 |
  | 3.6872        | 449.8 | 900  | 3.4371          | 1.0 |
  | 3.6892        | 499.8 | 1000 | 3.4337          | 1.0 |
  | 3.684         | 549.8 | 1100 | 3.4375          | 1.0 |
  | 3.6843        | 599.8 | 1200 | 3.4452          | 1.0 |
  | 3.6842        | 649.8 | 1300 | 3.4416          | 1.0 |
  | 3.6819        | 699.8 | 1400 | 3.4498          | 1.0 |
  | 3.6832        | 749.8 | 1500 | 3.4524          | 1.0 |
  | 3.6828        | 799.8 | 1600 | 3.4495          | 1.0 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  