readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: week5-eng-distilbert-base-multilingual-cased-finetuned
    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. -->
  
  # week5-eng-distilbert-base-multilingual-cased-finetuned
  
  This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0855
  - Precision: 0.2813
  - Recall: 0.2949
  - F1: 0.2880
  - Accuracy: 0.9763
  
  ## 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: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.1071        | 1.0   | 924  | 0.0911          | 0.2472    | 0.0444 | 0.0753 | 0.9755   |
  | 0.07          | 2.0   | 1848 | 0.0891          | 0.3206    | 0.1697 | 0.2219 | 0.9775   |
  | 0.0522        | 3.0   | 2772 | 0.0855          | 0.2813    | 0.2949 | 0.2880 | 0.9763   |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  