readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - recall
  - f1
  model-index:
  - name: distil_bert_uncased-finetuned-relations
    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. -->
  
  # distil_bert_uncased-finetuned-relations
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4191
  - Accuracy: 0.8866
  - Prec: 0.8771
  - Recall: 0.8866
  - F1: 0.8808
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Prec   | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|
  | 1.1823        | 1.0   | 232  | 0.5940          | 0.8413   | 0.8273 | 0.8413 | 0.8224 |
  | 0.4591        | 2.0   | 464  | 0.4600          | 0.8607   | 0.8539 | 0.8607 | 0.8555 |
  | 0.3106        | 3.0   | 696  | 0.4160          | 0.8812   | 0.8763 | 0.8812 | 0.8785 |
  | 0.246         | 4.0   | 928  | 0.4113          | 0.8834   | 0.8766 | 0.8834 | 0.8796 |
  | 0.2013        | 5.0   | 1160 | 0.4191          | 0.8866   | 0.8771 | 0.8866 | 0.8808 |
  
  
  ### Framework versions
  
  - Transformers 4.19.4
  - Pytorch 1.13.0.dev20220614
  - Datasets 2.2.2
  - Tokenizers 0.11.6
  