readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: olm-bert-tiny-december-2022-target-glue-qqp
    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. -->
  
  # olm-bert-tiny-december-2022-target-glue-qqp
  
  This model is a fine-tuned version of [muhtasham/olm-bert-tiny-december-2022](https://huggingface.co/muhtasham/olm-bert-tiny-december-2022) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5217
  - Accuracy: 0.7433
  - F1: 0.6048
  
  ## 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 | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.6283        | 0.04  | 500  | 0.5955          | 0.6795   | 0.5186 |
  | 0.5875        | 0.09  | 1000 | 0.5763          | 0.6972   | 0.5596 |
  | 0.5791        | 0.13  | 1500 | 0.5690          | 0.6975   | 0.6011 |
  | 0.5666        | 0.18  | 2000 | 0.5536          | 0.7156   | 0.5520 |
  | 0.5568        | 0.22  | 2500 | 0.5447          | 0.7230   | 0.5709 |
  | 0.5489        | 0.26  | 3000 | 0.5386          | 0.7281   | 0.5665 |
  | 0.5465        | 0.31  | 3500 | 0.5305          | 0.7329   | 0.5917 |
  | 0.5384        | 0.35  | 4000 | 0.5262          | 0.7357   | 0.6231 |
  | 0.5422        | 0.4   | 4500 | 0.5207          | 0.7409   | 0.6200 |
  | 0.5299        | 0.44  | 5000 | 0.5217          | 0.7433   | 0.6048 |
  
  
  ### Framework versions
  
  - Transformers 4.27.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.1.dev0
  - Tokenizers 0.13.2
  