readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: small-mlm-wikitext-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-wikitext-from-scratch-custom-tokenizer-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/small-mlm-wikitext-from-scratch-custom-tokenizer](https://huggingface.co/muhtasham/small-mlm-wikitext-from-scratch-custom-tokenizer) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3135
  - Precision: 0.5394
  - Recall: 0.6932
  - F1: 0.6067
  - Accuracy: 0.9205
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.6115        | 1.14  | 500  | 0.4596          | 0.2964    | 0.4574 | 0.3597 | 0.8598   |
  | 0.3787        | 2.28  | 1000 | 0.3634          | 0.3690    | 0.5017 | 0.4252 | 0.8889   |
  | 0.293         | 3.42  | 1500 | 0.3407          | 0.3956    | 0.5751 | 0.4688 | 0.8944   |
  | 0.238         | 4.56  | 2000 | 0.3159          | 0.4337    | 0.5774 | 0.4953 | 0.9034   |
  | 0.1975        | 5.69  | 2500 | 0.3061          | 0.4729    | 0.6033 | 0.5302 | 0.9104   |
  | 0.1655        | 6.83  | 3000 | 0.3045          | 0.4851    | 0.6427 | 0.5529 | 0.9128   |
  | 0.1392        | 7.97  | 3500 | 0.2934          | 0.5052    | 0.6508 | 0.5688 | 0.9170   |
  | 0.1127        | 9.11  | 4000 | 0.3047          | 0.5228    | 0.6781 | 0.5904 | 0.9184   |
  | 0.0945        | 10.25 | 4500 | 0.3047          | 0.5471    | 0.6712 | 0.6028 | 0.9234   |
  | 0.0802        | 11.39 | 5000 | 0.3135          | 0.5394    | 0.6932 | 0.6067 | 0.9205   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  