readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: tiny-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. -->
  
  # tiny-mlm-wikitext-from-scratch-custom-tokenizer-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-wikitext-from-scratch-custom-tokenizer](https://huggingface.co/muhtasham/tiny-mlm-wikitext-from-scratch-custom-tokenizer) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3451
  - Precision: 0.3914
  - Recall: 0.5631
  - F1: 0.4618
  - Accuracy: 0.8978
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 1.0009        | 1.14  | 500  | 0.6888          | 0.1156    | 0.1160 | 0.1158 | 0.8144   |
  | 0.6084        | 2.28  | 1000 | 0.5797          | 0.2110    | 0.2735 | 0.2382 | 0.8417   |
  | 0.5231        | 3.42  | 1500 | 0.5113          | 0.2567    | 0.3295 | 0.2886 | 0.8560   |
  | 0.4552        | 4.56  | 2000 | 0.4575          | 0.2947    | 0.4061 | 0.3415 | 0.8701   |
  | 0.4           | 5.69  | 2500 | 0.4172          | 0.3182    | 0.4615 | 0.3767 | 0.8802   |
  | 0.3587        | 6.83  | 3000 | 0.3915          | 0.3378    | 0.4921 | 0.4006 | 0.8871   |
  | 0.3263        | 7.97  | 3500 | 0.3719          | 0.3638    | 0.5296 | 0.4313 | 0.8918   |
  | 0.2975        | 9.11  | 4000 | 0.3605          | 0.3687    | 0.5411 | 0.4385 | 0.8939   |
  | 0.2748        | 10.25 | 4500 | 0.3509          | 0.3868    | 0.5471 | 0.4532 | 0.8969   |
  | 0.2602        | 11.39 | 5000 | 0.3451          | 0.3914    | 0.5631 | 0.4618 | 0.8978   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  