readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: 20NG_ALBERT_5E
    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. -->
  
  # 20NG_ALBERT_5E
  
  This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2209
  - Accuracy: 0.6067
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 2.8602        | 0.07  | 50   | 2.5794          | 0.2133   |
  | 2.3635        | 0.14  | 100  | 2.0956          | 0.38     |
  | 2.1526        | 0.21  | 150  | 1.9011          | 0.4467   |
  | 1.9014        | 0.28  | 200  | 1.6340          | 0.5067   |
  | 1.6736        | 0.35  | 250  | 1.5457          | 0.5467   |
  | 1.5563        | 0.42  | 300  | 1.5041          | 0.5533   |
  | 1.4338        | 0.49  | 350  | 1.3933          | 0.5933   |
  | 1.3348        | 0.56  | 400  | 1.4123          | 0.54     |
  | 1.2879        | 0.64  | 450  | 1.3352          | 0.6333   |
  | 1.2864        | 0.71  | 500  | 1.3027          | 0.62     |
  | 1.2162        | 0.78  | 550  | 1.2734          | 0.6267   |
  | 1.1786        | 0.85  | 600  | 1.2695          | 0.5933   |
  | 1.1702        | 0.92  | 650  | 1.2379          | 0.5933   |
  | 1.2338        | 0.99  | 700  | 1.2209          | 0.6067   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  