readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: Heem/distilroberta-finetuned-wtner
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
  probably proofread and complete it, then remove this comment. -->
  
  # Heem/distilroberta-finetuned-wtner
  
  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.0055
  - Validation Loss: 0.4521
  - Train Precision: 0.7410
  - Train Recall: 0.8122
  - Train F1: 0.775
  - Train Accuracy: 0.9382
  - Epoch: 69
  
  ## 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:
  - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2030, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
  - training_precision: float32
  
  ### Training results
  
  | Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
  |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
  | 1.3579     | 0.8909          | 0.0             | 0.0          | 0.0      | 0.7744         | 0     |
  | 0.7332     | 0.6231          | 0.3526          | 0.2926       | 0.3198   | 0.8256         | 1     |
  | 0.5037     | 0.4471          | 0.3927          | 0.3755       | 0.3839   | 0.8575         | 2     |
  | 0.3675     | 0.3776          | 0.484           | 0.5284       | 0.5052   | 0.8855         | 3     |
  | 0.2890     | 0.3519          | 0.5149          | 0.6026       | 0.5553   | 0.9039         | 4     |
  | 0.2367     | 0.3317          | 0.5820          | 0.6507       | 0.6144   | 0.9150         | 5     |
  | 0.1942     | 0.2970          | 0.6220          | 0.6900       | 0.6542   | 0.9237         | 6     |
  | 0.1599     | 0.3040          | 0.6375          | 0.6681       | 0.6525   | 0.9217         | 7     |
  | 0.1281     | 0.3037          | 0.6774          | 0.7336       | 0.7044   | 0.9304         | 8     |
  | 0.1097     | 0.3127          | 0.708           | 0.7729       | 0.7390   | 0.9309         | 9     |
  | 0.0915     | 0.3114          | 0.6836          | 0.7642       | 0.7216   | 0.9290         | 10    |
  | 0.0765     | 0.3190          | 0.7072          | 0.8122       | 0.7561   | 0.9372         | 11    |
  | 0.0665     | 0.3169          | 0.7154          | 0.7904       | 0.7510   | 0.9353         | 12    |
  | 0.0543     | 0.3251          | 0.7059          | 0.7860       | 0.7438   | 0.9329         | 13    |
  | 0.0472     | 0.3307          | 0.7181          | 0.8122       | 0.7623   | 0.9357         | 14    |
  | 0.0427     | 0.3639          | 0.7148          | 0.7991       | 0.7546   | 0.9357         | 15    |
  | 0.0380     | 0.3373          | 0.7373          | 0.8210       | 0.7769   | 0.9377         | 16    |
  | 0.0380     | 0.3422          | 0.7449          | 0.8035       | 0.7731   | 0.9372         | 17    |
  | 0.0304     | 0.3455          | 0.7530          | 0.8122       | 0.7815   | 0.9386         | 18    |
  | 0.0271     | 0.3584          | 0.7294          | 0.8122       | 0.7686   | 0.9377         | 19    |
  | 0.0249     | 0.3661          | 0.7291          | 0.7991       | 0.7625   | 0.9377         | 20    |
  | 0.0205     | 0.3683          | 0.7352          | 0.8122       | 0.7718   | 0.9391         | 21    |
  | 0.0212     | 0.3855          | 0.7331          | 0.8035       | 0.7667   | 0.9382         | 22    |
  | 0.0188     | 0.3814          | 0.7419          | 0.8035       | 0.7715   | 0.9391         | 23    |
  | 0.0189     | 0.3889          | 0.7352          | 0.8122       | 0.7718   | 0.9357         | 24    |
  | 0.0161     | 0.3913          | 0.7379          | 0.7991       | 0.7673   | 0.9382         | 25    |
  | 0.0154     | 0.3872          | 0.7470          | 0.8122       | 0.7782   | 0.9406         | 26    |
  | 0.0144     | 0.3934          | 0.7326          | 0.8253       | 0.7762   | 0.9401         | 27    |
  | 0.0154     | 0.4167          | 0.7255          | 0.8079       | 0.7645   | 0.9343         | 28    |
  | 0.0135     | 0.3976          | 0.7341          | 0.8079       | 0.7692   | 0.9362         | 29    |
  | 0.0119     | 0.4118          | 0.7510          | 0.8297       | 0.7884   | 0.9382         | 30    |
  | 0.0103     | 0.4112          | 0.7323          | 0.8122       | 0.7702   | 0.9372         | 31    |
  | 0.0103     | 0.4172          | 0.7362          | 0.8166       | 0.7743   | 0.9382         | 32    |
  | 0.0111     | 0.4157          | 0.7283          | 0.8079       | 0.7660   | 