readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: sentence-compression
    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. -->
  
  # sentence-compression
  
  This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2973
  - Accuracy: 0.8912
  - F1: 0.8367
  - Precision: 0.8495
  - Recall: 0.8243
  
  ## 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: 16
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 0.2686        | 1.0   | 10000 | 0.2667          | 0.8894   | 0.8283 | 0.8725    | 0.7884 |
  | 0.2205        | 2.0   | 20000 | 0.2704          | 0.8925   | 0.8372 | 0.8579    | 0.8175 |
  | 0.1476        | 3.0   | 30000 | 0.2973          | 0.8912   | 0.8367 | 0.8495    | 0.8243 |
  
  
  ### Framework versions
  
  - Transformers 4.12.5
  - Pytorch 1.10.0+cu113
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  