readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: small-mlm-tweet_eval-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-tweet_eval-from-scratch-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/small-mlm-tweet_eval-from-scratch](https://huggingface.co/muhtasham/small-mlm-tweet_eval-from-scratch) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2818
  - Precision: 0.6288
  - Recall: 0.7415
  - F1: 0.6805
  - Accuracy: 0.9349
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.6126        | 1.14  | 500  | 0.4262          | 0.3594    | 0.4480 | 0.3988 | 0.8717   |
  | 0.3588        | 2.28  | 1000 | 0.3324          | 0.4554    | 0.5830 | 0.5113 | 0.8995   |
  | 0.2618        | 3.42  | 1500 | 0.3179          | 0.4530    | 0.6437 | 0.5318 | 0.8997   |
  | 0.204         | 4.56  | 2000 | 0.2764          | 0.5381    | 0.6424 | 0.5857 | 0.9177   |
  | 0.162         | 5.69  | 2500 | 0.2695          | 0.5752    | 0.6658 | 0.6172 | 0.9244   |
  | 0.13          | 6.83  | 3000 | 0.2556          | 0.5682    | 0.7035 | 0.6287 | 0.9260   |
  | 0.1027        | 7.97  | 3500 | 0.2557          | 0.5946    | 0.7220 | 0.6521 | 0.9294   |
  | 0.0811        | 9.11  | 4000 | 0.2638          | 0.6097    | 0.7154 | 0.6584 | 0.9325   |
  | 0.0648        | 10.25 | 4500 | 0.2745          | 0.6105    | 0.7324 | 0.6659 | 0.9325   |
  | 0.0533        | 11.39 | 5000 | 0.2818          | 0.6288    | 0.7415 | 0.6805 | 0.9349   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  