readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: rubert-base-cased-sentence-finetuned-sent_in_news_sents
    results:
    - task:
        name: Text Classification
        type: text-classification
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.7224199288256228
      - name: F1
        type: f1
        value: 0.5137303178348194
  ---
  
  <!-- 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-sent_in_news_sents
  
  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: 1.9506
  - Accuracy: 0.7224
  - F1: 0.5137
  
  ## 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: 5e-05
  - train_batch_size: 14
  - eval_batch_size: 14
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | No log        | 1.0   | 81   | 1.0045          | 0.6690   | 0.1388 |
  | No log        | 2.0   | 162  | 0.9574          | 0.6228   | 0.2980 |
  | No log        | 3.0   | 243  | 1.0259          | 0.6477   | 0.3208 |
  | No log        | 4.0   | 324  | 1.1262          | 0.6619   | 0.4033 |
  | No log        | 5.0   | 405  | 1.3377          | 0.6299   | 0.3909 |
  | No log        | 6.0   | 486  | 1.5716          | 0.6868   | 0.3624 |
  | 0.6085        | 7.0   | 567  | 1.6286          | 0.6762   | 0.4130 |
  | 0.6085        | 8.0   | 648  | 1.6450          | 0.6940   | 0.4775 |
  | 0.6085        | 9.0   | 729  | 1.7108          | 0.7224   | 0.4920 |
  | 0.6085        | 10.0  | 810  | 1.8792          | 0.7046   | 0.5028 |
  | 0.6085        | 11.0  | 891  | 1.8670          | 0.7153   | 0.4992 |
  | 0.6085        | 12.0  | 972  | 1.8856          | 0.7153   | 0.4934 |
  | 0.0922        | 13.0  | 1053 | 1.9506          | 0.7224   | 0.5137 |
  | 0.0922        | 14.0  | 1134 | 2.0363          | 0.7189   | 0.4761 |
  | 0.0922        | 15.0  | 1215 | 2.0601          | 0.7224   | 0.5053 |
  | 0.0922        | 16.0  | 1296 | 2.0813          | 0.7153   | 0.5038 |
  | 0.0922        | 17.0  | 1377 | 2.0960          | 0.7189   | 0.5065 |
  | 0.0922        | 18.0  | 1458 | 2.1060          | 0.7224   | 0.5098 |
  | 0.0101        | 19.0  | 1539 | 2.1153          | 0.7260   | 0.5086 |
  | 0.0101        | 20.0  | 1620 | 2.1187          | 0.7260   | 0.5086 |
  
  
  ### Framework versions
  
  - Transformers 4.10.3
  - Pytorch 1.9.0+cu102
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  