readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model_index:
    name: albert-xxlarge-v2-finetuned-csqa-ih
  ---
  
  <!-- 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. -->
  
  # albert-xxlarge-v2-finetuned-csqa-ih
  
  This model is a fine-tuned version of [albert-xxlarge-v2](https://huggingface.co/albert-xxlarge-v2) on an unkown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.5694
  - Accuracy: 0.8026
  
  ## 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: 1e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.8032        | 1.0   | 532  | 0.5217          | 0.8043   |
  | 0.3182        | 2.0   | 1064 | 0.6313          | 0.7985   |
  | 0.0668        | 3.0   | 1596 | 1.2971          | 0.7969   |
  | 0.0131        | 4.0   | 2128 | 1.4671          | 0.8026   |
  | 0.0046        | 5.0   | 2660 | 1.5694          | 0.8026   |
  
  
  ### Framework versions
  
  - Transformers 4.8.2
  - Pytorch 1.9.0
  - Datasets 1.10.2
  - Tokenizers 0.10.3
  