readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: deberta-v3-large
    results: []
  ---
  
  # deberta-v3-large-irony
  
  This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an [tweet_eval](https://huggingface.co/datasets/tweet_eval)  dataset.
  
  ## Model description
  
  Test set results:
  
  | Model                      | Emotion       | Hate          | Irony         | Offensive     | Sentiment     | 
  | -------------              | ------------- | ------------- | ------------- | ------------- | ------------- | 
  | deberta-v3-large           | **86.3**      | **61.3**      | **87.1**      | **86.4**      | **73.9**      | 
  | BERTweet                   | 79.3          | -             | 82.1          | 79.5          | 73.4          | 
  | RoB-RT                     | 79.5          | 52.3          | 61.7          | 80.5          | 69.3          | 
  
  [source:papers_with_code](https://paperswithcode.com/sota/sentiment-analysis-on-tweeteval)
  
  
  ## Intended uses & limitations
  
  Classifying attributes of interest on tweeter like data. 
  
  ## Training and evaluation data
  
  [tweet_eval](https://huggingface.co/datasets/tweet_eval)  dataset.
  
  ## Training procedure
  
  Fine tuned and evaluated with [run_glue.py]()
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 8e-06
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 50
  - num_epochs: 10.0
  - label_smoothing_factor: 0.1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6478        | 1.12  | 100  | 0.5890          | 0.7529   |
  | 0.5013        | 2.25  | 200  | 0.5873          | 0.7707   |
  | 0.388         | 3.37  | 300  | 0.6993          | 0.7602   |
  | 0.3169        | 4.49  | 400  | 0.6773          | 0.7874   |
  | 0.2693        | 5.61  | 500  | 0.7172          | 0.7707   |
  | 0.2396        | 6.74  | 600  | 0.7397          | 0.7801   |
  | 0.2284        | 7.86  | 700  | 0.8096          | 0.7550   |
  | 0.2207        | 8.98  | 800  | 0.7827          | 0.7654   |
  
  
  ### Framework versions
  
  - Transformers 4.20.0.dev0
  - Pytorch 1.9.0
  - Datasets 2.2.2
  - Tokenizers 0.11.6
  