readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: tiny-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. -->
  
  # tiny-mlm-tweet_eval-from-scratch-custom-tokenizer-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-tweet_eval-from-scratch-custom-tokenizer](https://huggingface.co/muhtasham/tiny-mlm-tweet_eval-from-scratch-custom-tokenizer) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4153
  - Precision: 0.2618
  - Recall: 0.4002
  - F1: 0.3166
  - Accuracy: 0.8656
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 1.0571        | 1.14  | 500  | 0.7799          | 0.0549    | 0.0559 | 0.0554 | 0.7879   |
  | 0.6857        | 2.28  | 1000 | 0.6491          | 0.1028    | 0.1508 | 0.1222 | 0.8120   |
  | 0.6016        | 3.42  | 1500 | 0.5834          | 0.1427    | 0.2189 | 0.1728 | 0.8256   |
  | 0.5481        | 4.56  | 2000 | 0.5410          | 0.1707    | 0.2654 | 0.2078 | 0.8366   |
  | 0.5078        | 5.69  | 2500 | 0.5046          | 0.1888    | 0.3080 | 0.2341 | 0.8467   |
  | 0.474         | 6.83  | 3000 | 0.4732          | 0.2181    | 0.3477 | 0.2681 | 0.8552   |
  | 0.4435        | 7.97  | 3500 | 0.4505          | 0.2310    | 0.3814 | 0.2877 | 0.8593   |
  | 0.4168        | 9.11  | 4000 | 0.4369          | 0.2343    | 0.3851 | 0.2913 | 0.8611   |
  | 0.3965        | 10.25 | 4500 | 0.4222          | 0.2431    | 0.4000 | 0.3024 | 0.8636   |
  | 0.3829        | 11.39 | 5000 | 0.4153          | 0.2618    | 0.4002 | 0.3166 | 0.8656   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  