readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: QuBERTa-finetuned-pos
    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. -->
  
  # QuBERTa-finetuned-pos
  
  This model is a fine-tuned version of [Llamacha/QuBERTa](https://huggingface.co/Llamacha/QuBERTa) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4249
  - Precision: 0.8372
  - Recall: 0.8702
  - F1: 0.8534
  - Accuracy: 0.8623
  
  ## 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: 2e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 152  | 0.6146          | 0.6876    | 0.7482 | 0.7167 | 0.7360   |
  | No log        | 2.0   | 304  | 0.4937          | 0.7554    | 0.8041 | 0.7790 | 0.7932   |
  | No log        | 3.0   | 456  | 0.4525          | 0.7920    | 0.8238 | 0.8076 | 0.8200   |
  | 0.5624        | 4.0   | 608  | 0.4294          | 0.8144    | 0.8426 | 0.8283 | 0.8391   |
  | 0.5624        | 5.0   | 760  | 0.4245          | 0.8192    | 0.8521 | 0.8353 | 0.8445   |
  | 0.5624        | 6.0   | 912  | 0.4357          | 0.8201    | 0.8607 | 0.8399 | 0.8480   |
  | 0.3064        | 7.0   | 1064 | 0.4240          | 0.8308    | 0.8694 | 0.8497 | 0.8582   |
  | 0.3064        | 8.0   | 1216 | 0.4231          | 0.8406    | 0.8757 | 0.8578 | 0.8653   |
  | 0.3064        | 9.0   | 1368 | 0.4202          | 0.8389    | 0.8686 | 0.8535 | 0.8617   |
  | 0.2227        | 10.0  | 1520 | 0.4249          | 0.8372    | 0.8702 | 0.8534 | 0.8623   |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  