readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: small-mlm-conll2003-from-scratch-custom-tokenizer-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-custom-tokenizer-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/small-mlm-conll2003-from-scratch-custom-tokenizer](https://huggingface.co/muhtasham/small-mlm-conll2003-from-scratch-custom-tokenizer) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3448
  - Precision: 0.5713
  - Recall: 0.6853
  - F1: 0.6231
  - Accuracy: 0.9188
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.5039        | 1.14  | 500  | 0.4083          | 0.4419    | 0.4899 | 0.4647 | 0.8780   |
  | 0.3033        | 2.28  | 1000 | 0.3461          | 0.4899    | 0.5717 | 0.5276 | 0.8962   |
  | 0.2307        | 3.42  | 1500 | 0.3217          | 0.4619    | 0.6373 | 0.5356 | 0.9006   |
  | 0.182         | 4.56  | 2000 | 0.3198          | 0.4844    | 0.6530 | 0.5562 | 0.9045   |
  | 0.1502        | 5.69  | 2500 | 0.3146          | 0.5239    | 0.6528 | 0.5813 | 0.9104   |
  | 0.1265        | 6.83  | 3000 | 0.3216          | 0.4999    | 0.6755 | 0.5746 | 0.9071   |
  | 0.1042        | 7.97  | 3500 | 0.3151          | 0.5320    | 0.6666 | 0.5918 | 0.9138   |
  | 0.0873        | 9.11  | 4000 | 0.3378          | 0.5443    | 0.6839 | 0.6062 | 0.9139   |
  | 0.0723        | 10.25 | 4500 | 0.3487          | 0.5488    | 0.6781 | 0.6066 | 0.9140   |
  | 0.0636        | 11.39 | 5000 | 0.3448          | 0.5713    | 0.6853 | 0.6231 | 0.9188   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  