readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: SST2_XLNet_5E
    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. -->
  
  # SST2_XLNet_5E
  
  This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5502
  - Accuracy: 0.9133
  
  ## 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
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6038        | 0.12  | 50   | 0.2830          | 0.8933   |
  | 0.3903        | 0.23  | 100  | 0.3346          | 0.9      |
  | 0.3476        | 0.35  | 150  | 0.4187          | 0.8533   |
  | 0.3528        | 0.46  | 200  | 0.3177          | 0.9      |
  | 0.3372        | 0.58  | 250  | 0.4171          | 0.8333   |
  | 0.3106        | 0.69  | 300  | 0.2825          | 0.9      |
  | 0.295         | 0.81  | 350  | 0.3152          | 0.9      |
  | 0.2828        | 0.92  | 400  | 0.4360          | 0.88     |
  | 0.2359        | 1.04  | 450  | 0.3971          | 0.9      |
  | 0.2224        | 1.15  | 500  | 0.3380          | 0.88     |
  | 0.2136        | 1.27  | 550  | 0.3889          | 0.8933   |
  | 0.264         | 1.39  | 600  | 0.4182          | 0.8667   |
  | 0.1864        | 1.5   | 650  | 0.4887          | 0.88     |
  | 0.1817        | 1.62  | 700  | 0.3626          | 0.9133   |
  | 0.2021        | 1.73  | 750  | 0.4481          | 0.8933   |
  | 0.2154        | 1.85  | 800  | 0.3702          | 0.8933   |
  | 0.2392        | 1.96  | 850  | 0.5025          | 0.8933   |
  | 0.1496        | 2.08  | 900  | 0.4606          | 0.9133   |
  | 0.1537        | 2.19  | 950  | 0.5008          | 0.8933   |
  | 0.1015        | 2.31  | 1000 | 0.5612          | 0.9067   |
  | 0.0915        | 2.42  | 1050 | 0.5249          | 0.8933   |
  | 0.1239        | 2.54  | 1100 | 0.4234          | 0.9133   |
  | 0.1135        | 2.66  | 1150 | 0.4910          | 0.9067   |
  | 0.1738        | 2.77  | 1200 | 0.3844          | 0.92     |
  | 0.1428        | 2.89  | 1250 | 0.4282          | 0.92     |
  | 0.1282        | 3.0   | 1300 | 0.4320          | 0.9      |
  | 0.059         | 3.12  | 1350 | 0.4957          | 0.9133   |
  | 0.0517        | 3.23  | 1400 | 0.4927          | 0.92     |
  | 0.0853        | 3.35  | 1450 | 0.4187          | 0.92     |
  | 0.0808        | 3.46  | 1500 | 0.4304          | 0.92     |
  | 0.09          | 3.58  | 1550 | 0.3447          | 0.9267   |
  | 0.044         | 3.7   | 1600 | 0.4994          | 0.9067   |
  | 0.0443        | 3.81  | 1650 | 0.4516          | 0.9133   |
  | 0.0974        | 3.93  | 1700 | 0.4172          | 0.92     |
  | 0.0768        | 4.04  | 1750 | 0.4777          | 0.9133   |
  | 0.0418        | 4.16  | 1800 | 0.4924          | 0.9267   |
  | 0.0237        | 4.27  | 1850 | 0.5254          | 0.92     |
  | 0.0426        | 4.39  | 1900 | 0.5532          | 0.9133   |
  | 0.0336        | 4.5   | 1950 | 0.5838          | 0.9067   |
  | 0.0188        | 4.62  | 2000 | 0.5775          | 0.9067   |
  | 0.0318        | 4.73  | 2050 | 0.5781          | 0.9067   |
  | 0.0348        | 4.85  | 2100 | 0.5526          | 0.9133   |
  | 0.0524        | 4.97  | 2150 | 0.5502          | 0.9133   |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.13.0
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  