readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: distilbert-base-uncased-finetuned-legal_data
    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. -->
  
  # distilbert-base-uncased-finetuned-legal_data
  
  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: 6.9101
  
  ## 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: 100
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | No log        | 1.0   | 26   | 5.3529          |
  | No log        | 2.0   | 52   | 5.4226          |
  | No log        | 3.0   | 78   | 5.2550          |
  | No log        | 4.0   | 104  | 5.1011          |
  | No log        | 5.0   | 130  | 5.1857          |
  | No log        | 6.0   | 156  | 5.5119          |
  | No log        | 7.0   | 182  | 5.4480          |
  | No log        | 8.0   | 208  | 5.6993          |
  | No log        | 9.0   | 234  | 5.9614          |
  | No log        | 10.0  | 260  | 5.6987          |
  | No log        | 11.0  | 286  | 5.6679          |
  | No log        | 12.0  | 312  | 5.9850          |
  | No log        | 13.0  | 338  | 5.6065          |
  | No log        | 14.0  | 364  | 5.3162          |
  | No log        | 15.0  | 390  | 5.7856          |
  | No log        | 16.0  | 416  | 5.5786          |
  | No log        | 17.0  | 442  | 5.6028          |
  | No log        | 18.0  | 468  | 5.7649          |
  | No log        | 19.0  | 494  | 5.5382          |
  | 1.8345        | 20.0  | 520  | 6.3654          |
  | 1.8345        | 21.0  | 546  | 5.3575          |
  | 1.8345        | 22.0  | 572  | 5.3808          |
  | 1.8345        | 23.0  | 598  | 5.9340          |
  | 1.8345        | 24.0  | 624  | 6.1475          |
  | 1.8345        | 25.0  | 650  | 6.2188          |
  | 1.8345        | 26.0  | 676  | 5.7651          |
  | 1.8345        | 27.0  | 702  | 6.2629          |
  | 1.8345        | 28.0  | 728  | 6.1356          |
  | 1.8345        | 29.0  | 754  | 5.9255          |
  | 1.8345        | 30.0  | 780  | 6.4252          |
  | 1.8345        | 31.0  | 806  | 5.6967          |
  | 1.8345        | 32.0  | 832  | 6.4324          |
  | 1.8345        | 33.0  | 858  | 6.5087          |
  | 1.8345        | 34.0  | 884  | 6.1113          |
  | 1.8345        | 35.0  | 910  | 6.7443          |
  | 1.8345        | 36.0  | 936  | 6.6970          |
  | 1.8345        | 37.0  | 962  | 6.5578          |
  | 1.8345        | 38.0  | 988  | 6.1963          |
  | 0.2251        | 39.0  | 1014 | 6.4893          |
  | 0.2251        | 40.0  | 1040 | 6.6347          |
  | 0.2251        | 41.0  | 1066 | 6.7106          |
  | 0.2251        | 42.0  | 1092 | 6.8129          |
  | 0.2251        | 43.0  | 1118 | 6.6386          |
  | 0.2251        | 44.0  | 1144 | 6.4134          |
  | 0.2251        | 45.0  | 1170 | 6.6883          |
  | 0.2251        | 46.0  | 1196 | 6.6406          |
  | 0.2251        | 47.0  | 1222 | 6.3065          |
  | 0.2251        | 48.0  | 1248 | 7.0281          |
  | 0.2251        | 49.0  | 1274 | 7.3646          |
  | 0.2251        | 50.0  | 1300 | 7.1086          |
  | 0.2251        | 51.0  | 1326 | 6.4749          |
  | 0.2251        | 52.0  | 1352 | 6.3303          |
  | 0.2251        | 53.0  | 1378 | 6.2919          |
  | 0.2251        | 54.0  | 1404 | 6.3855          |
  | 0.2251        | 55.0  | 1430 | 6.9501          |
  | 0.2251        | 56.0  | 1456 | 6.8714          |
  | 0.2251        | 57.0  | 1482 | 6.9856          |
  | 0.0891        | 58.0  | 1508 | 6.9910          |
  | 0.0891        | 59.0  | 1534 | 6.9293          |
  | 0.0891        | 60.0  | 1560 | 7.3493          |
  | 0.0891        | 61.0  | 1586 | 7.1834          |
  | 0.0891        | 62.0  | 1612 | 7.0479          |
  | 0.0891        | 63.0  | 1638 | 6.7674          |
  | 0.0891        | 64.0  | 1664 | 6.7553          |
  | 0.0891        | 65.0  | 1690 | 7.3074          |
  | 0.0891        | 66.0  | 1716 | 6.8071          |
  | 0.0891        | 67.0  | 1742 | 7.6622          |
  | 0.0891        | 68.0  | 1768 | 6.9555          |
  | 0.0891        | 69.0  | 1794 | 7.0153          |
  | 0.0891        | 70.0  | 1820 | 7.2085          |
  | 0.0891        | 71.0  | 1846 | 6.7582          |
  | 0.0891        | 72.0  | 1872 | 6.7989          |
  | 0.0891        | 73.0  | 1898 | 6.7012          |
  | 0.0891        | 74.0  | 1924 | 7.0088          |
  | 0.0891        | 75.0  | 1950 | 7.1024          |
  | 0.0891    