readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: small-mlm-imdb-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-imdb-from-scratch-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/small-mlm-imdb-from-scratch](https://huggingface.co/muhtasham/small-mlm-imdb-from-scratch) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3139
  - Precision: 0.5483
  - Recall: 0.7058
  - F1: 0.6172
  - Accuracy: 0.9221
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.5923        | 1.14  | 500  | 0.4204          | 0.3729    | 0.4786 | 0.4192 | 0.8745   |
  | 0.3516        | 2.28  | 1000 | 0.3429          | 0.4295    | 0.5677 | 0.4890 | 0.8961   |
  | 0.2674        | 3.42  | 1500 | 0.3151          | 0.4455    | 0.6234 | 0.5196 | 0.9042   |
  | 0.2144        | 4.56  | 2000 | 0.3141          | 0.4764    | 0.6176 | 0.5379 | 0.9088   |
  | 0.1759        | 5.69  | 2500 | 0.3065          | 0.5075    | 0.6503 | 0.5701 | 0.9134   |
  | 0.1493        | 6.83  | 3000 | 0.2908          | 0.5103    | 0.6737 | 0.5807 | 0.9160   |
  | 0.1234        | 7.97  | 3500 | 0.2949          | 0.5192    | 0.6770 | 0.5877 | 0.9189   |
  | 0.1022        | 9.11  | 4000 | 0.3015          | 0.5398    | 0.6865 | 0.6044 | 0.9207   |
  | 0.0859        | 10.25 | 4500 | 0.3145          | 0.5227    | 0.7025 | 0.5994 | 0.9195   |
  | 0.0735        | 11.39 | 5000 | 0.3139          | 0.5483    | 0.7058 | 0.6172 | 0.9221   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  