readme: ---
  license: apache-2.0
  tags:
  - text-classification
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: nmp
    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. -->
  
  # nmp
  
  This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on the custom dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0803
  - Accuracy: 0.9688
  
  ## 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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 19   | 1.4407          | 0.3438   |
  | No log        | 2.0   | 38   | 0.6772          | 0.9375   |
  | No log        | 3.0   | 57   | 0.2852          | 0.9688   |
  | No log        | 4.0   | 76   | 0.0846          | 1.0      |
  | No log        | 5.0   | 95   | 0.0803          | 0.9688   |
  | No log        | 6.0   | 114  | 0.1039          | 0.9688   |
  | No log        | 7.0   | 133  | 0.1371          | 0.9688   |
  | No log        | 8.0   | 152  | 0.1239          | 0.9688   |
  | No log        | 9.0   | 171  | 0.1325          | 0.9688   |
  | No log        | 10.0  | 190  | 0.1312          | 0.9688   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  