readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - new_dataset
  metrics:
  - accuracy
  model-index:
  - name: wav2vec2-base-finetuned-manthan_base
    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_base
  
  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: 1.2246
  - Accuracy: 0.9691
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 2.4725        | 0.98  | 12   | 2.4222          | 0.1057   |
  | 2.4501        | 1.98  | 24   | 2.2420          | 0.2784   |
  | 2.2977        | 2.98  | 36   | 2.0155          | 0.7603   |
  | 2.1331        | 3.98  | 48   | 1.8193          | 0.8582   |
  | 1.7927        | 4.98  | 60   | 1.6376          | 0.9459   |
  | 1.7226        | 5.98  | 72   | 1.4940          | 0.9613   |
  | 1.6036        | 6.98  | 84   | 1.3632          | 0.9665   |
  | 1.5181        | 7.98  | 96   | 1.2963          | 0.9562   |
  | 1.4384        | 8.98  | 108  | 1.2406          | 0.9742   |
  | 1.3339        | 9.98  | 120  | 1.2246          | 0.9691   |
  
  
  ### Framework versions
  
  - Transformers 4.19.0
  - Pytorch 1.11.0+cu113
  - Datasets 1.14.0
  - Tokenizers 0.12.1
  