readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: deberta-v3-large__sst2__train-8-9
    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. -->
  
  # deberta-v3-large__sst2__train-8-9
  
  This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6013
  - Accuracy: 0.7210
  
  ## 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: 2e-05
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 50
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6757        | 1.0   | 3    | 0.7810          | 0.25     |
  | 0.6506        | 2.0   | 6    | 0.8102          | 0.25     |
  | 0.6463        | 3.0   | 9    | 0.8313          | 0.25     |
  | 0.5813        | 4.0   | 12   | 0.8858          | 0.25     |
  | 0.4635        | 5.0   | 15   | 0.8220          | 0.25     |
  | 0.3992        | 6.0   | 18   | 0.7226          | 0.5      |
  | 0.3281        | 7.0   | 21   | 0.6707          | 0.75     |
  | 0.2276        | 8.0   | 24   | 0.7515          | 0.75     |
  | 0.1674        | 9.0   | 27   | 0.6971          | 0.75     |
  | 0.0873        | 10.0  | 30   | 0.5419          | 0.75     |
  | 0.0525        | 11.0  | 33   | 0.5025          | 0.75     |
  | 0.0286        | 12.0  | 36   | 0.5229          | 0.75     |
  | 0.0149        | 13.0  | 39   | 0.5660          | 0.75     |
  | 0.0082        | 14.0  | 42   | 0.6954          | 0.75     |
  | 0.006         | 15.0  | 45   | 0.8649          | 0.75     |
  | 0.0043        | 16.0  | 48   | 1.0011          | 0.75     |
  | 0.0035        | 17.0  | 51   | 1.0909          | 0.75     |
  | 0.0021        | 18.0  | 54   | 1.1615          | 0.75     |
  | 0.0017        | 19.0  | 57   | 1.2147          | 0.75     |
  | 0.0013        | 20.0  | 60   | 1.2585          | 0.75     |
  | 0.0016        | 21.0  | 63   | 1.2917          | 0.75     |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2
  - Tokenizers 0.10.3
  