readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: tiny-mlm-snli-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-snli-from-scratch-custom-tokenizer-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-snli-from-scratch-custom-tokenizer](https://huggingface.co/muhtasham/tiny-mlm-snli-from-scratch-custom-tokenizer) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4949
  - Precision: 0.1811
  - Recall: 0.2837
  - F1: 0.2211
  - Accuracy: 0.8401
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 1.1064        | 1.14  | 500  | 0.8667          | 0.0151    | 0.0165 | 0.0157 | 0.7660   |
  | 0.7755        | 2.28  | 1000 | 0.7543          | 0.0452    | 0.0653 | 0.0534 | 0.7853   |
  | 0.702         | 3.42  | 1500 | 0.6770          | 0.0724    | 0.1080 | 0.0867 | 0.8021   |
  | 0.643         | 4.56  | 2000 | 0.6336          | 0.0973    | 0.1782 | 0.1259 | 0.8063   |
  | 0.6062        | 5.69  | 2500 | 0.5967          | 0.1146    | 0.2020 | 0.1462 | 0.8143   |
  | 0.5808        | 6.83  | 3000 | 0.5672          | 0.1282    | 0.2198 | 0.1619 | 0.8222   |
  | 0.5564        | 7.97  | 3500 | 0.5431          | 0.1404    | 0.2450 | 0.1786 | 0.8270   |
  | 0.5315        | 9.11  | 4000 | 0.5236          | 0.1478    | 0.2622 | 0.1891 | 0.8309   |
  | 0.5137        | 10.25 | 4500 | 0.5095          | 0.1557    | 0.2777 | 0.1995 | 0.8338   |
  | 0.4978        | 11.39 | 5000 | 0.4949          | 0.1811    | 0.2837 | 0.2211 | 0.8401   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  