readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: olm-bert-tiny-december-2022-target-glue-mrpc
    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-mrpc
  
  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: 0.9243
  - Accuracy: 0.6299
  - F1: 0.7146
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.6093        | 4.35  | 500  | 0.5848          | 0.7034   | 0.7980 |
  | 0.5487        | 8.7   | 1000 | 0.5863          | 0.7206   | 0.8087 |
  | 0.4724        | 13.04 | 1500 | 0.6881          | 0.6544   | 0.7294 |
  | 0.3752        | 17.39 | 2000 | 0.7549          | 0.6520   | 0.7331 |
  | 0.276         | 21.74 | 2500 | 0.9243          | 0.6299   | 0.7146 |
  
  
  ### Framework versions
  
  - Transformers 4.27.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.1.dev0
  - Tokenizers 0.13.2
  