readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - spearmanr
  model-index:
  - name: olm-bert-tiny-december-2022-target-glue-stsb
    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-stsb
  
  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: 2.4058
  - Pearson: 0.3207
  - Spearmanr: 0.3227
  
  ## 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 | Pearson | Spearmanr |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|
  | 3.7225        | 2.78  | 500  | 2.3571          | 0.0394  | 0.0504    |
  | 1.9638        | 5.56  | 1000 | 2.3486          | 0.1721  | 0.1893    |
  | 1.7812        | 8.33  | 1500 | 2.3649          | 0.2248  | 0.2401    |
  | 1.5724        | 11.11 | 2000 | 2.3334          | 0.2645  | 0.2767    |
  | 1.3776        | 13.89 | 2500 | 2.4034          | 0.2785  | 0.2861    |
  | 1.2174        | 16.67 | 3000 | 2.3773          | 0.2963  | 0.3043    |
  | 1.0875        | 19.44 | 3500 | 2.3327          | 0.3213  | 0.3205    |
  | 0.9406        | 22.22 | 4000 | 2.3715          | 0.3216  | 0.3222    |
  | 0.8757        | 25.0  | 4500 | 2.3264          | 0.3274  | 0.3281    |
  | 0.7946        | 27.78 | 5000 | 2.4058          | 0.3207  | 0.3227    |
  
  
  ### Framework versions
  
  - Transformers 4.27.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.1.dev0
  - Tokenizers 0.13.2
  