readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: tiny-mlm-rotten_tomatoes-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-rotten_tomatoes-from-scratch-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-rotten_tomatoes-from-scratch](https://huggingface.co/muhtasham/tiny-mlm-rotten_tomatoes-from-scratch) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3273
  - Precision: 0.4485
  - Recall: 0.6124
  - F1: 0.5178
  - Accuracy: 0.9043
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 1.0073        | 1.14  | 500  | 0.6977          | 0.2294    | 0.1414 | 0.1749 | 0.8160   |
  | 0.5898        | 2.28  | 1000 | 0.5510          | 0.2488    | 0.2842 | 0.2654 | 0.8478   |
  | 0.5001        | 3.42  | 1500 | 0.4898          | 0.3060    | 0.3724 | 0.3359 | 0.8610   |
  | 0.439         | 4.56  | 2000 | 0.4415          | 0.3554    | 0.4377 | 0.3923 | 0.8757   |
  | 0.3893        | 5.69  | 2500 | 0.4050          | 0.3638    | 0.4864 | 0.4162 | 0.8847   |
  | 0.352         | 6.83  | 3000 | 0.3792          | 0.3903    | 0.5226 | 0.4468 | 0.8913   |
  | 0.3169        | 7.97  | 3500 | 0.3567          | 0.4060    | 0.5613 | 0.4712 | 0.8956   |
  | 0.2884        | 9.11  | 4000 | 0.3452          | 0.4174    | 0.5865 | 0.4877 | 0.8982   |
  | 0.264         | 10.25 | 4500 | 0.3346          | 0.4316    | 0.5899 | 0.4985 | 0.9012   |
  | 0.2502        | 11.39 | 5000 | 0.3273          | 0.4485    | 0.6124 | 0.5178 | 0.9043   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  