readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: CV11_finetuning1
    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. -->
  
  # CV11_finetuning1
  
  This model is a fine-tuned version of [Roshana/Wav2Vec1_CV](https://huggingface.co/Roshana/Wav2Vec1_CV) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7162
  - Wer: 0.3625
  
  ## 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: 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: 500
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.5067        | 0.86  | 400  | 0.6193          | 0.4492 |
  | 0.4448        | 1.72  | 800  | 0.6325          | 0.4384 |
  | 0.3781        | 2.59  | 1200 | 0.6248          | 0.4197 |
  | 0.3172        | 3.45  | 1600 | 0.6408          | 0.4343 |
  | 0.2556        | 4.31  | 2000 | 0.6593          | 0.4230 |
  | 0.2148        | 5.17  | 2400 | 0.6742          | 0.3987 |
  | 0.1779        | 6.03  | 2800 | 0.6658          | 0.3929 |
  | 0.1446        | 6.9   | 3200 | 0.6768          | 0.3846 |
  | 0.1248        | 7.76  | 3600 | 0.6809          | 0.3804 |
  | 0.108         | 8.62  | 4000 | 0.7214          | 0.3683 |
  | 0.0938        | 9.48  | 4400 | 0.7162          | 0.3625 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  