readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: distilbert_oscarth_0100
    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. -->
  
  # distilbert_oscarth_0100
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 1.0777
  - Validation Loss: 1.0396
  - Epoch: 99
  
  ## 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': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
  - training_precision: float32
  
  ### Training results
  
  | Train Loss | Validation Loss | Epoch |
  |:----------:|:---------------:|:-----:|
  | 4.1327     | 2.9983          | 0     |
  | 2.7813     | 2.4562          | 1     |
  | 2.4194     | 2.2066          | 2     |
  | 2.2231     | 2.0562          | 3     |
  | 2.0894     | 1.9450          | 4     |
  | 1.9905     | 1.8621          | 5     |
  | 1.9148     | 1.7941          | 6     |
  | 1.8508     | 1.7363          | 7     |
  | 1.7976     | 1.6909          | 8     |
  | 1.7509     | 1.6488          | 9     |
  | 1.7126     | 1.6124          | 10    |
  | 1.6764     | 1.5835          | 11    |
  | 1.6450     | 1.5521          | 12    |
  | 1.6175     | 1.5282          | 13    |
  | 1.5919     | 1.5045          | 14    |
  | 1.5679     | 1.4833          | 15    |
  | 1.5476     | 1.4627          | 16    |
  | 1.5271     | 1.4498          | 17    |
  | 1.5098     | 1.4270          | 18    |
  | 1.4909     | 1.4161          | 19    |
  | 1.4760     | 1.3995          | 20    |
  | 1.4609     | 1.3864          | 21    |
  | 1.4475     | 1.3717          | 22    |
  | 1.4333     | 1.3590          | 23    |
  | 1.4203     | 1.3478          | 24    |
  | 1.4093     | 1.3403          | 25    |
  | 1.3980     | 1.3296          | 26    |
  | 1.3875     | 1.3176          | 27    |
  | 1.3773     | 1.3094          | 28    |
  | 1.3674     | 1.3011          | 29    |
  | 1.3579     | 1.2920          | 30    |
  | 1.3497     | 1.2826          | 31    |
  | 1.3400     | 1.2764          | 32    |
  | 1.3326     | 1.2694          | 33    |
  | 1.3236     | 1.2635          | 34    |
  | 1.3169     | 1.2536          | 35    |
  | 1.3096     | 1.2477          | 36    |
  | 1.3024     | 1.2408          | 37    |
  | 1.2957     | 1.2364          | 38    |
  | 1.2890     | 1.2296          | 39    |
  | 1.2818     | 1.2236          | 40    |
  | 1.2751     | 1.2168          | 41    |
  | 1.2691     | 1.2126          | 42    |
  | 1.2644     | 1.2044          | 43    |
  | 1.2583     | 1.2008          | 44    |
  | 1.2529     | 1.1962          | 45    |
  | 1.2473     | 1.1919          | 46    |
  | 1.2416     | 1.1857          | 47    |
  | 1.2365     | 1.1812          | 48    |
  | 1.2318     | 1.1765          | 49    |
  | 1.2273     | 1.1738          | 50    |
  | 1.2224     | 1.1672          | 51    |
  | 1.2177     | 1.1673          | 52    |
  | 1.2132     | 1.1595          | 53    |
  | 1.2084     | 1.1564          | 54    |
  | 1.2033     | 1.1518          | 55    |
  | 1.1993     | 1.1481          | 56    |
  | 1.1966     | 1.1445          | 57    |
  | 1.1924     | 1.1412          | 58    |
  | 1.1876     | 1.1378          | 59    |
  | 1.1834     | 1.1340          | 60    |
  | 1.1806     | 1.1329          | 61    |
  | 1.1783     | 1.1289          | 62    |
  | 1.1739     | 1.1251          | 63    |
  | 1.1705     | 1.1223          | 64    |
  | 1.1669     | 1.1192          | 65    |
  | 1.1628     | 1.1172          | 66    |
  | 1.1599     | 1.1140          | 67    |
  | 1.1570     | 1.1084          | 68    |
  | 1.1526     | 1.1081          | 69    |
  | 1.1496     | 1.1043          | 70    |
  | 1.1463     | 1.0999          | 71    |
  | 1.1438     | 1.1006          | 72    |
  | 1.1397     | 1.0964          | 73    |
  | 1.1378     | 1.0918          | 74    |
  | 1.1347     | 1.0917          | 75    |
  | 1.1319     | 1.0889          | 76    |
  | 1.1296     | 1.0855          | 77    |
  | 1.1271     | 1.0848          | 78    |
  | 1.1236     | 1.0821          | 79    |
  | 1.1212     | 1.0801          | 80    |
  | 1.1185     | 1.0771          | 81    |
  | 1.1155     | 1.0750          | 82    |
  | 1.1139     | 1.0726          | 83    |
  | 1.1110     | 1.0713          | 84    |
  | 1.1082     | 1.0689          | 85    |
  | 1.1057     | 1.0658          | 86    |
  | 1.1031     | 1.0641          | 87    |
  | 1.1018     | 1.0619          | 88    |
  | 1.0985     | 1.0606          | 89    |
  | 1.0976     | 1.0590          | 90    |
  | 1.0944     | 1.0570          | 91    |
  | 1.0926     | 1.0561          | 92    |
  | 1.0905     | 1.05