readme: ---
  language: en
  tags: 
  - deberta-v1
  - deberta-mnli
  tasks: mnli
  thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
  license: mit
  pipeline_tag: zero-shot-classification
  ---
  
  This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the GLUE MNLI dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4103
  - Accuracy: 0.9175
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 6e-06
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 50
  - num_epochs: 2.0
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.3631        | 1.0   | 49088 | 0.3129          | 0.9130   |
  | 0.2267        | 2.0   | 98176 | 0.4157          | 0.9153   |
  
  
  ### Framework versions
  
  - Transformers 4.13.0.dev0
  - Pytorch 1.10.0
  - Datasets 1.15.2.dev0
  - Tokenizers 0.10.3
  