readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: roberta-large-all-dataset
    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. -->
  
  # roberta-large-all-dataset
  
  This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on the None dataset.
  It achieves the following results on the evaluation set:
  - Exact Match: 77.1769
  - F1: 85.6178
  - Loss: 0.5347
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 32
  - total_train_batch_size: 256
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  - label_smoothing_factor: 0.1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Exact Match | F1      | Validation Loss |
  |:-------------:|:-----:|:----:|:-----------:|:-------:|:---------------:|
  | 3.7417        | 1.5   | 672  | 68.5244     | 78.5098 | 1.1172          |
  | 0.889         | 3.0   | 1344 | 74.5613     | 83.7411 | 0.6406          |
  | 0.6361        | 4.5   | 2016 | 76.3492     | 84.9826 | 0.5654          |
  | 0.5696        | 6.0   | 2688 | 76.6472     | 85.2937 | 0.5493          |
  | 0.5461        | 7.5   | 3360 | 76.7906     | 85.3519 | 0.5415          |
  | 0.5349        | 9.0   | 4032 | 77.1769     | 85.6178 | 0.5347          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  