readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: rubert-base-cased-sentence-finetuned-headlines_X
    results:
    - task:
        name: Text Classification
        type: text-classification
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.952
  ---
  
  <!-- 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. -->
  
  # rubert-base-cased-sentence-finetuned-headlines_X
  
  This model is a fine-tuned version of [DeepPavlov/rubert-base-cased-sentence](https://huggingface.co/DeepPavlov/rubert-base-cased-sentence) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2535
  - Accuracy: 0.952
  
  ## 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: 32
  - eval_batch_size: 32
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 157  | 0.2759          | 0.912    |
  | No log        | 2.0   | 314  | 0.2538          | 0.936    |
  | No log        | 3.0   | 471  | 0.2556          | 0.945    |
  | 0.1908        | 4.0   | 628  | 0.2601          | 0.95     |
  | 0.1908        | 5.0   | 785  | 0.2535          | 0.952    |
  
  
  ### Framework versions
  
  - Transformers 4.10.2
  - Pytorch 1.9.0+cu102
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  