readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: small-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. -->
  
  # small-mlm-conll2003-from-scratch-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/small-mlm-conll2003-from-scratch](https://huggingface.co/muhtasham/small-mlm-conll2003-from-scratch) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3026
  - Precision: 0.6374
  - Recall: 0.7129
  - F1: 0.6730
  - Accuracy: 0.9340
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.5707        | 1.14  | 500  | 0.3994          | 0.3895    | 0.4650 | 0.4239 | 0.8806   |
  | 0.3406        | 2.28  | 1000 | 0.3272          | 0.4662    | 0.5498 | 0.5046 | 0.9016   |
  | 0.257         | 3.42  | 1500 | 0.3064          | 0.4490    | 0.6331 | 0.5254 | 0.9043   |
  | 0.2033        | 4.56  | 2000 | 0.2905          | 0.5185    | 0.6311 | 0.5693 | 0.9154   |
  | 0.1636        | 5.69  | 2500 | 0.2773          | 0.5457    | 0.6585 | 0.5969 | 0.9213   |
  | 0.1333        | 6.83  | 3000 | 0.2734          | 0.5615    | 0.6880 | 0.6183 | 0.9247   |
  | 0.1072        | 7.97  | 3500 | 0.2737          | 0.5653    | 0.6863 | 0.6199 | 0.9263   |
  | 0.0848        | 9.11  | 4000 | 0.2800          | 0.5913    | 0.7095 | 0.6450 | 0.9290   |
  | 0.0687        | 10.25 | 4500 | 0.2878          | 0.6002    | 0.7164 | 0.6532 | 0.9302   |
  | 0.0568        | 11.39 | 5000 | 0.3026          | 0.6374    | 0.7129 | 0.6730 | 0.9340   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  