readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - new_dataset
  metrics:
  - accuracy
  model-index:
  - name: wav2vec2-base-finetuned-manthan-gujarati-digits
    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-base-finetuned-manthan-gujarati-digits
  
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the new_dataset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5613
  - Accuracy: 0.9923
  
  ## 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: 3e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.3392        | 0.98  | 12   | 1.1315          | 0.9665   |
  | 1.2319        | 1.98  | 24   | 0.9487          | 0.9716   |
  | 1.0824        | 2.98  | 36   | 0.8338          | 0.9820   |
  | 0.9995        | 3.98  | 48   | 0.7533          | 0.9845   |
  | 0.8175        | 4.98  | 60   | 0.6759          | 0.9923   |
  | 0.8015        | 5.98  | 72   | 0.6425          | 0.9845   |
  | 0.7417        | 6.98  | 84   | 0.6048          | 0.9871   |
  | 0.7181        | 7.98  | 96   | 0.5850          | 0.9923   |
  | 0.6907        | 8.98  | 108  | 0.5687          | 0.9897   |
  | 0.6511        | 9.98  | 120  | 0.5613          | 0.9923   |
  
  
  ### Framework versions
  
  - Transformers 4.19.0
  - Pytorch 1.11.0+cu113
  - Datasets 1.14.0
  - Tokenizers 0.12.1
  