readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: model_dir
    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. -->
  
  # model_dir
  
  This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0380
  - Pearson: 0.9399
  
  ## 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: 8e-05
  - train_batch_size: 128
  - eval_batch_size: 256
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Pearson |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | No log        | 1.0   | 12   | 0.2773          | 0.7230  |
  | No log        | 2.0   | 24   | 0.1120          | 0.7812  |
  | No log        | 3.0   | 36   | 0.1090          | 0.8638  |
  | No log        | 4.0   | 48   | 0.0613          | 0.9163  |
  | No log        | 5.0   | 60   | 0.0447          | 0.9409  |
  | No log        | 6.0   | 72   | 0.0356          | 0.9402  |
  | No log        | 7.0   | 84   | 0.0368          | 0.9359  |
  | No log        | 8.0   | 96   | 0.0408          | 0.9295  |
  | No log        | 9.0   | 108  | 0.0397          | 0.9382  |
  | No log        | 10.0  | 120  | 0.0380          | 0.9399  |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  