readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: sentence_bert-base-uncased-finetuned-SENTENCE
    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. -->
  
  # sentence_bert-base-uncased-finetuned-SENTENCE
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4834
  - Precision: 0.8079
  - Recall: 1.0
  - F1: 0.8938
  - Accuracy: 0.8079
  
  ## 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: 0.0001
  - 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 | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 13   | 0.3520          | 0.8889    | 1.0    | 0.9412 | 0.8889   |
  | No log        | 2.0   | 26   | 0.3761          | 0.8889    | 1.0    | 0.9412 | 0.8889   |
  | No log        | 3.0   | 39   | 0.3683          | 0.8889    | 1.0    | 0.9412 | 0.8889   |
  | No log        | 4.0   | 52   | 0.3767          | 0.8889    | 1.0    | 0.9412 | 0.8889   |
  | No log        | 5.0   | 65   | 0.3834          | 0.8889    | 1.0    | 0.9412 | 0.8889   |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.1+cu113
  - Datasets 1.18.0
  - Tokenizers 0.10.3
  