readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: token_final_tunned
    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. -->
  
  # token_final_tunned
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4670
  - Precision: 0.8269
  - Recall: 0.8442
  - F1: 0.8355
  - Accuracy: 0.8516
  
  ## 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: 8
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 108  | 0.7286          | 0.6581    | 0.7117 | 0.6838 | 0.7272   |
  | No log        | 2.0   | 216  | 0.5497          | 0.7529    | 0.7823 | 0.7673 | 0.8053   |
  | No log        | 3.0   | 324  | 0.4884          | 0.7911    | 0.8145 | 0.8026 | 0.8277   |
  | No log        | 4.0   | 432  | 0.4723          | 0.8144    | 0.8278 | 0.8210 | 0.8408   |
  | 0.6038        | 5.0   | 540  | 0.4597          | 0.8032    | 0.8315 | 0.8171 | 0.8428   |
  | 0.6038        | 6.0   | 648  | 0.4583          | 0.8208    | 0.8322 | 0.8264 | 0.8480   |
  | 0.6038        | 7.0   | 756  | 0.4641          | 0.8290    | 0.8442 | 0.8365 | 0.8520   |
  | 0.6038        | 8.0   | 864  | 0.4670          | 0.8269    | 0.8442 | 0.8355 | 0.8516   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu102
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  