readme: ---
  language:
  - en
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  model-index:
  - name: deberta-v3-small
    results:
    - task:
        type: text-classification
        name: Text Classification
      dataset:
        name: GLUE QNLI
        type: glue
        args: qnli
      metrics:
      - type: accuracy
        value: 0.9150649826102873
        name: Accuracy
    - task:
        type: natural-language-inference
        name: Natural Language Inference
      dataset:
        name: glue
        type: glue
        config: qnli
        split: validation
      metrics:
      - type: accuracy
        value: 0.914881933003844
        name: Accuracy
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDY2NmRlOTEyMzkwMjc5MjVjZDY3MTczMmM2ZTEyZTFiMTk1YmJiYjkxYmYyYTAzNDlhOTU5OTMzZjhhMjkyMSIsInZlcnNpb24iOjF9.aoHEeaQLKI4uwmTgp8Lo9zRoParcSlyDiXZiRrWTqZJIMHgwKgQg52zvYYrZ9HMjjIvWjdW9G_s_DfxqBoekDA
      - type: precision
        value: 0.9195906432748538
        name: Precision
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMGMyMjUyNTliOWZjMzkzM2Y3YWU0ODhiNDcyOTAwZjYyZjRiNGQ5NTgyODM4Y2VjNGRlYzNkNTViNmJhNzM0ZSIsInZlcnNpb24iOjF9.fJdQ7M46RGvp_uXk9jvBpl0RFAIGTRAtk8bRQGjNn_uy5weBm6tENL-OclZHwG4uU6LviGTdXmAwn5Ba37hNBw
      - type: recall
        value: 0.9112640347700108
        name: Recall
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiM2Y2ZmIyZTMzMzM1MTc1OWQ0YWI2ZjU2MzQ5NGU1M2FjNDRiOWViM2NkNWU2M2UzZjljMDJjNmUzZTQ1YWM2MiIsInZlcnNpb24iOjF9.6kVxEkJ-Fojy9HgMevsHovimj3IYp97WO2991zQOFN8nEpPc0hThFk5kMRotS-jPSLFh0mS2PVhQ5x3HIo17Ag
      - type: auc
        value: 0.9718281171793548
        name: AUC
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMmZiMGU3MzVjMWNlOTViNmZlYmZjZDRmMzI4OGI4NzAxN2Y5OTE2YmVlMzEzY2ZmODBlODQ1ZjA5MTlhNmEzYyIsInZlcnNpb24iOjF9.byBFlu-eyAmwGQ_tkVi3zaSklTY4G6qenYu1b6hNvYlfPeCuBtVA6qJNF_DI4QWZyEBtdICIyYHzTUHGcAFUBg
      - type: f1
        value: 0.9154084045843187
        name: F1
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDdmZjk4MzRkMzgyMDY0MjZjZTZiYWNiMTE5MjBiMTBhYWQyYjVjYzk5Mzc1NzQxMGFkMzk4NDUzMjg1YmYzMCIsInZlcnNpb24iOjF9.zYUMpTtIHycUUa5ftwz3hjFb8xk0V5LaUbCDA679Q1BZtXZrEaXtSjbJNKiLBQip1gIwYC1aADcfgSELoBG8AA
      - type: loss
        value: 0.21421395242214203
        name: loss
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNGM1YjNiNWFmYzQ3NDJiZTlhNDZiNWIxMjc3M2I1OWJlYzkzYWJkNzVkZDdiNWY4YjNiZDM0NzYxZjQ1OGQ4NSIsInZlcnNpb24iOjF9.qI91L1kE_ZjSOktpGx3OolCkHZuP0isPgKy2EC-YB_M3LEDym4APHVUjhwCgYFCu3-LcVH8syQ7SmI4mrovDAw
  ---
  
  <!-- 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-small fine-tuned on QNLI
  
  This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the GLUE QNLI dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2143
  - Accuracy: 0.9151
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5.0
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.2823        | 1.0   | 6547  | 0.2143          | 0.9151   |
  | 0.1996        | 2.0   | 13094 | 0.2760          | 0.9103   |
  | 0.1327        | 3.0   | 19641 | 0.3293          | 0.9169   |
  | 0.0811        | 4.0   | 26188 | 0.4278          | 0.9193   |
  | 0.05          | 5.0   | 32735 | 0.5110          | 0.9176   |
  
  
  ### Framework versions
  
  - Transformers 4.13.0.dev0
  - Pytorch 1.10.0+cu111
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  