readme: ---
  language:
  - en
  license: mit
  tags:
  - generated_from_trainer
  - deberta-v3
  datasets:
  - glue
  metrics:
  - accuracy
  model-index:
  - name: deberta-v3-small
    results:
    - task:
        type: text-classification
        name: Text Classification
      dataset:
        name: GLUE SST2
        type: glue
        args: sst2
      metrics:
      - type: accuracy
        value: 0.9403669724770642
        name: Accuracy
    - task:
        type: text-classification
        name: Text Classification
      dataset:
        name: glue
        type: glue
        config: sst2
        split: validation
      metrics:
      - type: accuracy
        value: 0.9403669724770642
        name: Accuracy
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiM2MyOTE4ZTk0YzUyNGFkMGVjNTk4MDBlZGRlZjgzOGIzYWY0YjExMmZmMDZkYjFmOTlkYmM2ZDEwYjMxM2JkOCIsInZlcnNpb24iOjF9.Ks2vdjAFUe0isZp4F-OFK9HzvPqeU3mJEG_XJfOvkTdm9DyaefT9x78sof8i_EbIync5Ao7NOC4STCTQIUvgBw
      - type: precision
        value: 0.9375
        name: Precision
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzNiZTEwNGNlZWUwZjMxYmRjNWU0ZGQ1Njg1M2MwNTQ3YWEwN2JlNDk4OWQ4MzNkMmNhOGUwMzA0YWU3ZWZjMiIsInZlcnNpb24iOjF9.p5Gbs680U45zHoWH9YgRLmOxINR4emvc2yNe9Kt3-y_WyyCd6CAAK9ht-IyGJ7GSO5WQny-ISngJFtyFt5NqDQ
      - type: recall
        value: 0.9459459459459459
        name: Recall
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjk2MmJjMDZlZDUzM2QzMWZhMzMxNWRkYjJlYzA3MjUwMThiYWMwNmQzODE1MTMxNTdkNWVmMDhhNzJjMjg3MyIsInZlcnNpb24iOjF9.Jeu6tyhXQxMykqqFH0V-IXvyTrxAsgnYByYCOJgfj86957G5LiGdfQzDtTuGkt0XcoenXhPuueT8m5tsuJyLBA
      - type: auc
        value: 0.9804217184474193
        name: AUC
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiM2Q5MWU1MGMzMjEwNzY4MDkzN2Q5ZjM5MTQ2MDc5YTRkZTNmNTk2YTdhODI1ZGJlOTlkNTQ2M2Q4YTUxN2Y3OSIsInZlcnNpb24iOjF9.INkDvQhg2jfD7WEE4qHJazPYo10O4Ffc5AZz5vI8fmN01rK3sXzzydvmrmTMzYSSmLhn9sc1-ZkoWbcv81oqBA
      - type: f1
        value: 0.9417040358744394
        name: F1
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYWRhNjljZjk0NjY1ZjU1ZjU2ZmM5ODk1YTVkMTI0ZGY4MjI1OTFlZWJkZWMyMGYxY2I1MzRjODBkNGVlMzJkZSIsInZlcnNpb24iOjF9.kQ547NVFUxeE4vNiGzGsCvMxR1MCJTChX44ds27qQ4Rj2m1UuD2C9TLTuiu8KMvq1mH1io978dJEpOCHYq6KCQ
      - type: loss
        value: 0.21338027715682983
        name: loss
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiY2YyYmVhNzgxMzMyNjJiNzZkYjE1YWM5Y2ZmMTlkNjQ5MThhYjIxNTE5MmE3Y2E0ODllODMyYjAzYWI3ZWRlMSIsInZlcnNpb24iOjF9.ad9rLnOeJZbRi_QQKEBpNNBp_Bt5SHf39ZeWQOZxp7tAK9dc0OK8XOqtihoXcAWDahwuoGiiYtcFNtvueaX6DA
  ---
  
  <!-- 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 SST2
  
  This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the GLUE SST2 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2134
  - Accuracy: 0.9404
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.176         | 1.0   | 4210  | 0.2134          | 0.9404   |
  | 0.1254        | 2.0   | 8420  | 0.2362          | 0.9415   |
  | 0.0957        | 3.0   | 12630 | 0.3187          | 0.9335   |
  | 0.0673        | 4.0   | 16840 | 0.3039          | 0.9266   |
  | 0.0457        | 5.0   | 21050 | 0.3521          | 0.9312   |
  
  
  ### Framework versions
  
  - Transformers 4.13.0.dev0
  - Pytorch 1.10.0+cu111
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  