readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: wav2vec2-xlsr-korean-speech-emotion-recognition3
    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-xlsr-korean-speech-emotion-recognition3
  
  This model is a fine-tuned version of [jungjongho/wav2vec2-large-xlsr-korean-demo-colab_epoch15](https://huggingface.co/jungjongho/wav2vec2-large-xlsr-korean-demo-colab_epoch15) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0600
  - Accuracy: 0.9876
  
  ## 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: 2e-05
  - train_batch_size: 2
  - eval_batch_size: 2
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 4
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 1
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.6472        | 0.08  | 1500  | 0.3769          | 0.8705   |
  | 0.3873        | 0.15  | 3000  | 0.3814          | 0.9127   |
  | 0.3002        | 0.23  | 4500  | 0.2617          | 0.9429   |
  | 0.2399        | 0.3   | 6000  | 0.1336          | 0.9693   |
  | 0.2181        | 0.38  | 7500  | 0.1360          | 0.9728   |
  | 0.1992        | 0.46  | 9000  | 0.1239          | 0.9717   |
  | 0.1556        | 0.53  | 10500 | 0.1053          | 0.9781   |
  | 0.1412        | 0.61  | 12000 | 0.0915          | 0.9810   |
  | 0.1396        | 0.69  | 13500 | 0.0777          | 0.9826   |
  | 0.1159        | 0.76  | 15000 | 0.0801          | 0.9831   |
  | 0.1156        | 0.84  | 16500 | 0.0667          | 0.9867   |
  | 0.1149        | 0.91  | 18000 | 0.0670          | 0.9860   |
  | 0.0929        | 0.99  | 19500 | 0.0600          | 0.9876   |
  
  
  ### Framework versions
  
  - Transformers 4.22.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.1.dev0
  - Tokenizers 0.12.1
  