readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: SEMEVAL23_TASK3_SUBTASK1_MULTI
    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. -->
  
  # SEMEVAL23_TASK3_SUBTASK1_MULTI
  
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7683
  - F1: 0.6317
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.9869        | 1.0   | 40   | 0.9517          | 0.4244 |
  | 0.5569        | 2.0   | 80   | 0.7365          | 0.5514 |
  | 0.4559        | 3.0   | 120  | 0.7829          | 0.5348 |
  | 0.2018        | 4.0   | 160  | 0.6281          | 0.6241 |
  | 0.1125        | 5.0   | 200  | 0.9291          | 0.5614 |
  | 0.2594        | 6.0   | 240  | 1.0367          | 0.5884 |
  | 0.1883        | 7.0   | 280  | 0.7683          | 0.6317 |
  | 0.1083        | 8.0   | 320  | 0.8660          | 0.6106 |
  | 0.0659        | 9.0   | 360  | 0.8695          | 0.6189 |
  | 0.2554        | 10.0  | 400  | 1.0094          | 0.5839 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  