readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: address_parsing_test_1
    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. -->
  
  # address_parsing_test_1
  
  This model is a fine-tuned version of [csebuetnlp/banglabert](https://huggingface.co/csebuetnlp/banglabert) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0207
  - Precision: 0.9953
  - Recall: 0.9957
  - F1: 0.9955
  - Accuracy: 0.9963
  
  ## 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: 8
  - eval_batch_size: 8
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.0669        | 1.0   | 1266 | 0.0168          | 0.9890    | 0.9913 | 0.9902 | 0.9937   |
  | 0.02          | 2.0   | 2532 | 0.0132          | 0.9953    | 0.9961 | 0.9957 | 0.9967   |
  | 0.0122        | 3.0   | 3798 | 0.0177          | 0.9949    | 0.9955 | 0.9952 | 0.9962   |
  | 0.0068        | 4.0   | 5064 | 0.0181          | 0.9951    | 0.9957 | 0.9954 | 0.9963   |
  | 0.0048        | 5.0   | 6330 | 0.0207          | 0.9953    | 0.9957 | 0.9955 | 0.9963   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  