readme: ---
  license: agpl-3.0
  pipeline_tag: sentence-similarity
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - spearmanr
  model-index:
  - name: XLMR-ENIS-finetuned-stsb
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: glue
        type: glue
        args: stsb
      metrics:
      - name: Spearmanr
        type: spearmanr
        value: 0.8887885342806044
  ---
  
  <!-- 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. -->
  
  # XLMR-ENIS-finetuned-stsb
  
  This model is a fine-tuned version of [vesteinn/XLMR-ENIS](https://huggingface.co/vesteinn/XLMR-ENIS) on the glue dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5232
  - Pearson: 0.8915
  - Spearmanr: 0.8888
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|
  | No log        | 1.0   | 360  | 0.6330          | 0.8562  | 0.8570    |
  | 1.2835        | 2.0   | 720  | 0.6368          | 0.8790  | 0.8781    |
  | 0.4518        | 3.0   | 1080 | 0.5352          | 0.8883  | 0.8852    |
  | 0.4518        | 4.0   | 1440 | 0.4881          | 0.8910  | 0.8885    |
  | 0.288         | 5.0   | 1800 | 0.5232          | 0.8915  | 0.8888    |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.0+cu111
  - Datasets 1.13.0
  - Tokenizers 0.10.3
  