readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: small-mlm-rotten_tomatoes-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. -->
  
  # small-mlm-rotten_tomatoes-from-scratch-custom-tokenizer-target-conll2003
  
  This model is a fine-tuned version of [muhtasham/small-mlm-rotten_tomatoes-from-scratch-custom-tokenizer](https://huggingface.co/muhtasham/small-mlm-rotten_tomatoes-from-scratch-custom-tokenizer) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3065
  - Precision: 0.5377
  - Recall: 0.6510
  - F1: 0.5890
  - Accuracy: 0.9171
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.6635        | 1.14  | 500  | 0.4842          | 0.2323    | 0.3435 | 0.2771 | 0.8491   |
  | 0.438         | 2.28  | 1000 | 0.4003          | 0.2914    | 0.4507 | 0.3540 | 0.8705   |
  | 0.36          | 3.42  | 1500 | 0.3711          | 0.3166    | 0.5279 | 0.3959 | 0.8757   |
  | 0.3033        | 4.56  | 2000 | 0.3286          | 0.3780    | 0.5332 | 0.4423 | 0.8925   |
  | 0.2611        | 5.69  | 2500 | 0.3228          | 0.4091    | 0.5905 | 0.4833 | 0.8962   |
  | 0.2225        | 6.83  | 3000 | 0.3063          | 0.4403    | 0.6232 | 0.5160 | 0.9032   |
  | 0.1883        | 7.97  | 3500 | 0.2909          | 0.4681    | 0.6255 | 0.5355 | 0.9081   |
  | 0.156         | 9.11  | 4000 | 0.2942          | 0.4990    | 0.6425 | 0.5617 | 0.9117   |
  | 0.1314        | 10.25 | 4500 | 0.2981          | 0.5124    | 0.6669 | 0.5796 | 0.9143   |
  | 0.1122        | 11.39 | 5000 | 0.3065          | 0.5377    | 0.6510 | 0.5890 | 0.9171   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  