readme: ---
  tags:
  - generated_from_keras_callback
  model-index:
  - name: distilgpt_new_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. -->
  
  # distilgpt_new_0100
  
  This model was trained from scratch on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 1.0286
  - Validation Loss: 0.9952
  - 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 |
  |:----------:|:---------------:|:-----:|
  | 3.5889     | 2.6197          | 0     |
  | 2.4784     | 2.2040          | 1     |
  | 2.1855     | 1.9980          | 2     |
  | 2.0181     | 1.8643          | 3     |
  | 1.9031     | 1.7652          | 4     |
  | 1.8166     | 1.6924          | 5     |
  | 1.7467     | 1.6360          | 6     |
  | 1.6904     | 1.5843          | 7     |
  | 1.6430     | 1.5421          | 8     |
  | 1.6021     | 1.5059          | 9     |
  | 1.5668     | 1.4761          | 10    |
  | 1.5359     | 1.4481          | 11    |
  | 1.5071     | 1.4220          | 12    |
  | 1.4841     | 1.4020          | 13    |
  | 1.4608     | 1.3797          | 14    |
  | 1.4399     | 1.3595          | 15    |
  | 1.4213     | 1.3426          | 16    |
  | 1.4031     | 1.3266          | 17    |
  | 1.3875     | 1.3113          | 18    |
  | 1.3735     | 1.3024          | 19    |
  | 1.3600     | 1.2871          | 20    |
  | 1.3456     | 1.2753          | 21    |
  | 1.3336     | 1.2648          | 22    |
  | 1.3214     | 1.2539          | 23    |
  | 1.3103     | 1.2451          | 24    |
  | 1.3005     | 1.2335          | 25    |
  | 1.2905     | 1.2258          | 26    |
  | 1.2815     | 1.2179          | 27    |
  | 1.2728     | 1.2123          | 28    |
  | 1.2643     | 1.2029          | 29    |
  | 1.2564     | 1.1980          | 30    |
  | 1.2494     | 1.1877          | 31    |
  | 1.2414     | 1.1806          | 32    |
  | 1.2348     | 1.1788          | 33    |
  | 1.2290     | 1.1699          | 34    |
  | 1.2209     | 1.1654          | 35    |
  | 1.2156     | 1.1575          | 36    |
  | 1.2110     | 1.1537          | 37    |
  | 1.2046     | 1.1499          | 38    |
  | 1.1986     | 1.1436          | 39    |
  | 1.1940     | 1.1408          | 40    |
  | 1.1877     | 1.1356          | 41    |
  | 1.1830     | 1.1314          | 42    |
  | 1.1779     | 1.1278          | 43    |
  | 1.1737     | 1.1211          | 44    |
  | 1.1692     | 1.1192          | 45    |
  | 1.1647     | 1.1163          | 46    |
  | 1.1611     | 1.1107          | 47    |
  | 1.1560     | 1.1066          | 48    |
  | 1.1521     | 1.1060          | 49    |
  | 1.1489     | 1.1002          | 50    |
  | 1.1440     | 1.0960          | 51    |
  | 1.1406     | 1.0931          | 52    |
  | 1.1373     | 1.0897          | 53    |
  | 1.1329     | 1.0855          | 54    |
  | 1.1302     | 1.0842          | 55    |
  | 1.1265     | 1.0818          | 56    |
  | 1.1237     | 1.0784          | 57    |
  | 1.1204     | 1.0737          | 58    |
  | 1.1173     | 1.0714          | 59    |
  | 1.1140     | 1.0694          | 60    |
  | 1.1112     | 1.0691          | 61    |
  | 1.1083     | 1.0668          | 62    |
  | 1.1044     | 1.0611          | 63    |
  | 1.1027     | 1.0607          | 64    |
  | 1.0990     | 1.0586          | 65    |
  | 1.0969     | 1.0545          | 66    |
  | 1.0944     | 1.0522          | 67    |
  | 1.0921     | 1.0517          | 68    |
  | 1.0891     | 1.0496          | 69    |
  | 1.0862     | 1.0457          | 70    |
  | 1.0828     | 1.0448          | 71    |
  | 1.0824     | 1.0439          | 72    |
  | 1.0793     | 1.0389          | 73    |
  | 1.0769     | 1.0375          | 74    |
  | 1.0740     | 1.0362          | 75    |
  | 1.0717     | 1.0358          | 76    |
  | 1.0700     | 1.0299          | 77    |
  | 1.0675     | 1.0312          | 78    |
  | 1.0639     | 1.0288          | 79    |
  | 1.0643     | 1.0270          | 80    |
  | 1.0607     | 1.0258          | 81    |
  | 1.0602     | 1.0233          | 82    |
  | 1.0568     | 1.0225          | 83    |
  | 1.0557     | 1.0198          | 84    |
  | 1.0534     | 1.0179          | 85    |
  | 1.0512     | 1.0165          | 86    |
  | 1.0495     | 1.0170          | 87    |
  | 1.0478     | 1.0124          | 88    |
  | 1.0458     | 1.0134          | 89    |
  | 1.0439     | 1.0104          | 90    |
  | 1.0418     | 1.0092          | 91    |
  | 1.0401     | 1.0057          | 92    |
  | 1.0377     | 1.0035          | 93    |
  | 1.0370     | 1.0037          | 94    |
  | 1.0345     | 1.0029          | 95    |
  | 