readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: tiny-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. -->
  
  # tiny-mlm-conll2003-from-scratch-custom-tokenizer-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-conll2003-from-scratch-custom-tokenizer](https://huggingface.co/muhtasham/tiny-mlm-conll2003-from-scratch-custom-tokenizer) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3519
  - Precision: 0.4521
  - Recall: 0.5990
  - F1: 0.5152
  - Accuracy: 0.9001
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.9087        | 1.14  | 500  | 0.6605          | 0.2378    | 0.1520 | 0.1854 | 0.8258   |
  | 0.51          | 2.28  | 1000 | 0.5308          | 0.2599    | 0.3129 | 0.2839 | 0.8546   |
  | 0.4331        | 3.42  | 1500 | 0.4741          | 0.3499    | 0.4145 | 0.3795 | 0.8727   |
  | 0.3751        | 4.56  | 2000 | 0.4309          | 0.3909    | 0.4783 | 0.4302 | 0.8821   |
  | 0.3283        | 5.69  | 2500 | 0.4053          | 0.4271    | 0.5278 | 0.4721 | 0.8886   |
  | 0.2964        | 6.83  | 3000 | 0.3853          | 0.4342    | 0.5587 | 0.4887 | 0.8925   |
  | 0.2691        | 7.97  | 3500 | 0.3727          | 0.4417    | 0.5774 | 0.5005 | 0.8951   |
  | 0.2458        | 9.11  | 4000 | 0.3666          | 0.4253    | 0.5848 | 0.4925 | 0.8954   |
  | 0.2258        | 10.25 | 4500 | 0.3628          | 0.4514    | 0.5852 | 0.5096 | 0.8982   |
  | 0.2143        | 11.39 | 5000 | 0.3519          | 0.4521    | 0.5990 | 0.5152 | 0.9001   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  