readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: med_v1_M04_1e-05
    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. -->
  
  # med_v1_M04_1e-05
  
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.4848
  - Wer: 1.0
  - Cer: 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: 1e-05
  - train_batch_size: 20
  - 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: 18400
  - num_epochs: 2000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step   | Validation Loss | Wer | Cer |
  |:-------------:|:------:|:------:|:---------------:|:---:|:---:|
  | 38.6628       | 200.0  | 36800  | 3.4943          | 1.0 | 1.0 |
  | 3.1727        | 400.0  | 73600  | 3.4369          | 1.0 | 1.0 |
  | 3.0757        | 600.0  | 110400 | 3.4349          | 1.0 | 1.0 |
  | 3.0212        | 800.0  | 147200 | 3.4523          | 1.0 | 1.0 |
  | 2.9854        | 1000.0 | 184000 | 3.4652          | 1.0 | 1.0 |
  | 2.9605        | 1200.0 | 220800 | 3.4733          | 1.0 | 1.0 |
  | 2.943         | 1400.0 | 257600 | 3.4786          | 1.0 | 1.0 |
  | 2.9311        | 1600.0 | 294400 | 3.4810          | 1.0 | 1.0 |
  | 2.9235        | 1800.0 | 331200 | 3.4837          | 1.0 | 1.0 |
  | 2.92          | 2000.0 | 368000 | 3.4848          | 1.0 | 1.0 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.2+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  