readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - amazon_reviews_multi
  model-index:
  - name: xlm-roberta-base-finetuned-marc-en
    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-base-finetuned-marc-en
  
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the amazon_reviews_multi dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9161
  - Mae: 0.4634
  
  ## 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: 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: 2
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Mae    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.1217        | 1.0   | 235  | 0.9396          | 0.4878 |
  | 0.9574        | 2.0   | 470  | 0.9161          | 0.4634 |
  
  
  ### Framework versions
  
  - Transformers 4.14.1
  - Pytorch 1.10.0+cu111
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  