readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: small-mlm-tweet_eval-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-tweet_eval-from-scratch-custom-tokenizer-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/small-mlm-tweet_eval-from-scratch-custom-tokenizer](https://huggingface.co/muhtasham/small-mlm-tweet_eval-from-scratch-custom-tokenizer) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3269
  - Precision: 0.4715
  - Recall: 0.6299
  - F1: 0.5393
  - Accuracy: 0.9048
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.6782        | 1.14  | 500  | 0.5064          | 0.2100    | 0.3012 | 0.2475 | 0.8398   |
  | 0.4636        | 2.28  | 1000 | 0.4216          | 0.2659    | 0.4042 | 0.3208 | 0.8626   |
  | 0.3915        | 3.42  | 1500 | 0.3899          | 0.2693    | 0.4608 | 0.3399 | 0.8674   |
  | 0.3363        | 4.56  | 2000 | 0.3541          | 0.3403    | 0.4768 | 0.3972 | 0.8820   |
  | 0.2933        | 5.69  | 2500 | 0.3351          | 0.3719    | 0.5355 | 0.4389 | 0.8879   |
  | 0.2551        | 6.83  | 3000 | 0.3247          | 0.4078    | 0.5670 | 0.4744 | 0.8956   |
  | 0.2196        | 7.97  | 3500 | 0.3208          | 0.4562    | 0.5602 | 0.5029 | 0.9002   |
  | 0.1871        | 9.11  | 4000 | 0.3226          | 0.4834    | 0.5865 | 0.5300 | 0.9045   |
  | 0.1575        | 10.25 | 4500 | 0.3180          | 0.4671    | 0.6195 | 0.5326 | 0.9048   |
  | 0.1366        | 11.39 | 5000 | 0.3269          | 0.4715    | 0.6299 | 0.5393 | 0.9048   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  