readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: tiny-mlm-conll2003-from-scratch-target-conll2003
    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. -->
  
  # tiny-mlm-conll2003-from-scratch-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-conll2003-from-scratch](https://huggingface.co/muhtasham/tiny-mlm-conll2003-from-scratch) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3255
  - Precision: 0.4607
  - Recall: 0.6060
  - F1: 0.5234
  - Accuracy: 0.9053
  
  ## 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: 3e-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: constant
  - training_steps: 5000
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 1.0233        | 1.14  | 500  | 0.6786          | 0.1712    | 0.1419 | 0.1552 | 0.8249   |
  | 0.5801        | 2.28  | 1000 | 0.5489          | 0.2545    | 0.2928 | 0.2723 | 0.8497   |
  | 0.4936        | 3.42  | 1500 | 0.4847          | 0.3008    | 0.3612 | 0.3282 | 0.8619   |
  | 0.4297        | 4.56  | 2000 | 0.4325          | 0.3697    | 0.4478 | 0.4050 | 0.8785   |
  | 0.3753        | 5.69  | 2500 | 0.3901          | 0.3922    | 0.5126 | 0.4444 | 0.8892   |
  | 0.3337        | 6.83  | 3000 | 0.3638          | 0.4135    | 0.5401 | 0.4684 | 0.8958   |
  | 0.2989        | 7.97  | 3500 | 0.3460          | 0.4300    | 0.5786 | 0.4934 | 0.8993   |
  | 0.2716        | 9.11  | 4000 | 0.3359          | 0.4375    | 0.5890 | 0.5021 | 0.9022   |
  | 0.2493        | 10.25 | 4500 | 0.3320          | 0.4489    | 0.5867 | 0.5086 | 0.9035   |
  | 0.2374        | 11.39 | 5000 | 0.3255          | 0.4607    | 0.6060 | 0.5234 | 0.9053   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  