readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: small-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. -->
  
  # small-mlm-snli-from-scratch-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/small-mlm-snli-from-scratch](https://huggingface.co/muhtasham/small-mlm-snli-from-scratch) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2722
  - Precision: 0.6350
  - Recall: 0.7334
  - F1: 0.6807
  - Accuracy: 0.9355
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.5969        | 1.14  | 500  | 0.4174          | 0.3902    | 0.4960 | 0.4368 | 0.8740   |
  | 0.3356        | 2.28  | 1000 | 0.3105          | 0.4951    | 0.6070 | 0.5454 | 0.9055   |
  | 0.2397        | 3.42  | 1500 | 0.2794          | 0.4914    | 0.6572 | 0.5624 | 0.9120   |
  | 0.1822        | 4.56  | 2000 | 0.2548          | 0.5653    | 0.6718 | 0.6140 | 0.9241   |
  | 0.1443        | 5.69  | 2500 | 0.2484          | 0.5930    | 0.6816 | 0.6342 | 0.9280   |
  | 0.1151        | 6.83  | 3000 | 0.2457          | 0.5781    | 0.7060 | 0.6357 | 0.9291   |
  | 0.0927        | 7.97  | 3500 | 0.2430          | 0.6057    | 0.7174 | 0.6569 | 0.9320   |
  | 0.0739        | 9.11  | 4000 | 0.2645          | 0.6313    | 0.7078 | 0.6674 | 0.9349   |
  | 0.0606        | 10.25 | 4500 | 0.2651          | 0.6354    | 0.7218 | 0.6759 | 0.9359   |
  | 0.0506        | 11.39 | 5000 | 0.2722          | 0.6350    | 0.7334 | 0.6807 | 0.9355   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  