distilbert_new_0100 / README.md
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---
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 |
| 1.0339 | 1.0014 | 96 |
| 1.0322 | 1.0016 | 97 |
| 1.0296 | 0.9986 | 98 |
| 1.0286 | 0.9952 | 99 |
### Framework versions
- Transformers 4.20.1
- TensorFlow 2.8.2
- Datasets 2.3.2
- Tokenizers 0.12.1