readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - squad_v2
  model-index:
  - name: xlm-roberta-large-finetuned-squad-v2
    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. -->
  
  # xlm-roberta-large-finetuned-squad-v2
  
  This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the squad_v2 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4627
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 2.029         | 1.0   | 950  | 0.9281          |
  | 0.9774        | 2.0   | 1900 | 0.6130          |
  | 0.6781        | 3.0   | 2850 | 0.4627          |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.0+cu111
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  