readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: tiny-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. -->
  
  # tiny-mlm-tweet_eval-from-scratch-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-tweet_eval-from-scratch](https://huggingface.co/muhtasham/tiny-mlm-tweet_eval-from-scratch) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3264
  - Precision: 0.4495
  - Recall: 0.6040
  - F1: 0.5154
  - Accuracy: 0.9042
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.9795        | 1.14  | 500  | 0.6863          | 0.1677    | 0.1149 | 0.1364 | 0.8184   |
  | 0.5811        | 2.28  | 1000 | 0.5466          | 0.2383    | 0.2763 | 0.2559 | 0.8497   |
  | 0.4882        | 3.42  | 1500 | 0.4788          | 0.2979    | 0.3731 | 0.3313 | 0.8655   |
  | 0.4191        | 4.56  | 2000 | 0.4295          | 0.3581    | 0.4571 | 0.4016 | 0.8806   |
  | 0.3655        | 5.69  | 2500 | 0.3907          | 0.3819    | 0.5204 | 0.4405 | 0.8909   |
  | 0.3269        | 6.83  | 3000 | 0.3649          | 0.4069    | 0.5451 | 0.4659 | 0.8958   |
  | 0.2918        | 7.97  | 3500 | 0.3475          | 0.4203    | 0.5772 | 0.4865 | 0.8989   |
  | 0.266         | 9.11  | 4000 | 0.3396          | 0.4263    | 0.5816 | 0.4920 | 0.9011   |
  | 0.2457        | 10.25 | 4500 | 0.3319          | 0.4360    | 0.5867 | 0.5002 | 0.9025   |
  | 0.2318        | 11.39 | 5000 | 0.3264          | 0.4495    | 0.6040 | 0.5154 | 0.9042   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  