readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - minds14
  metrics:
  - wer
  model-index:
  - name: my_asr_model_3
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: minds14
        type: minds14
        config: en-US
        split: train[:100]
        args: en-US
      metrics:
      - name: Wer
        type: wer
        value: 1.0
  ---
  
  <!-- 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. -->
  
  # my_asr_model_3
  
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.8875
  - 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: 1e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 200
  - training_steps: 1000
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer |
  |:-------------:|:-----:|:----:|:---------------:|:---:|
  | 7.7043        | 60.0  | 300  | 6.0169          | 1.0 |
  | 4.5859        | 120.0 | 600  | 4.3190          | 1.0 |
  | 3.8087        | 180.0 | 900  | 3.8875          | 1.0 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  