readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: tiny-mlm-snli-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-snli-from-scratch-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-snli-from-scratch](https://huggingface.co/muhtasham/tiny-mlm-snli-from-scratch) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3282
  - Precision: 0.4518
  - Recall: 0.5961
  - F1: 0.5140
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.9955        | 1.14  | 500  | 0.7185          | 0.2123    | 0.1277 | 0.1595 | 0.8166   |
  | 0.6054        | 2.28  | 1000 | 0.5641          | 0.2535    | 0.2804 | 0.2663 | 0.8481   |
  | 0.5153        | 3.42  | 1500 | 0.5015          | 0.2936    | 0.3475 | 0.3183 | 0.8581   |
  | 0.4561        | 4.56  | 2000 | 0.4556          | 0.3416    | 0.4127 | 0.3738 | 0.8694   |
  | 0.4066        | 5.69  | 2500 | 0.4141          | 0.3547    | 0.4801 | 0.4080 | 0.8784   |
  | 0.3671        | 6.83  | 3000 | 0.3833          | 0.3941    | 0.5157 | 0.4467 | 0.8888   |
  | 0.3301        | 7.97  | 3500 | 0.3623          | 0.4062    | 0.5559 | 0.4694 | 0.8936   |
  | 0.2999        | 9.11  | 4000 | 0.3464          | 0.4132    | 0.5762 | 0.4813 | 0.8976   |
  | 0.2747        | 10.25 | 4500 | 0.3369          | 0.4332    | 0.5816 | 0.4966 | 0.9012   |
  | 0.2582        | 11.39 | 5000 | 0.3282          | 0.4518    | 0.5961 | 0.5140 | 0.9043   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  