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---
tags:
- generated_from_keras_callback
model-index:
- name: madatnlp/prefix-ket5-scratch
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. -->
# madatnlp/prefix-ket5-scratch
This model is a fine-tuned version of [madatnlp/ke-t5-math-py](https://huggingface.co/madatnlp/ke-t5-math-py) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.7214
- Validation Loss: 0.8747
- Epoch: 98
## 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': 'Adam', 'learning_rate': 1e-04, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 8.0101 | 5.1280 | 0 |
| 4.8040 | 3.6005 | 1 |
| 3.7550 | 2.8108 | 2 |
| 3.2740 | 2.6402 | 3 |
| 2.9682 | 2.3173 | 4 |
| 2.6871 | 2.1585 | 5 |
| 2.4782 | 2.0828 | 6 |
| 2.3507 | 1.9557 | 7 |
| 2.2131 | 1.8513 | 8 |
| 2.1235 | 1.6324 | 9 |
| 2.0157 | 1.6270 | 10 |
| 1.9722 | 1.6217 | 11 |
| 1.8733 | 1.5436 | 12 |
| 1.8680 | 1.5872 | 13 |
| 1.8365 | 1.6040 | 14 |
| 1.7528 | 1.5049 | 15 |
| 1.7411 | 1.4754 | 16 |
| 1.6733 | 1.4409 | 17 |
| 1.6544 | 1.4230 | 18 |
| 1.6271 | 1.4556 | 19 |
| 1.5658 | 1.3797 | 20 |
| 1.5774 | 1.3269 | 21 |
| 1.5150 | 1.3108 | 22 |
| 1.5057 | 1.3785 | 23 |
| 1.4605 | 1.3114 | 24 |
| 1.4702 | 1.2618 | 25 |
| 1.4220 | 1.2164 | 26 |
| 1.4194 | 1.2409 | 27 |
| 1.3942 | 1.2603 | 28 |
| 1.3921 | 1.3010 | 29 |
| 1.3645 | 1.1850 | 30 |
| 1.3336 | 1.1273 | 31 |
| 1.3499 | 1.1533 | 32 |
| 1.3022 | 1.1683 | 33 |
| 1.2990 | 1.1403 | 34 |
| 1.2876 | 1.1241 | 35 |
| 1.2479 | 1.0957 | 36 |
| 1.2441 | 1.1989 | 37 |
| 1.2464 | 1.1416 | 38 |
| 1.2353 | 1.0636 | 39 |
| 1.2152 | 1.1136 | 40 |
| 1.2212 | 1.0635 | 41 |
| 1.1892 | 1.0818 | 42 |
| 1.1959 | 1.1041 | 43 |
| 1.1957 | 1.0912 | 44 |
| 1.1542 | 1.0949 | 45 |
| 1.1403 | 1.1272 | 46 |
| 1.1396 | 1.1169 | 47 |
| 1.1149 | 1.0606 | 48 |
| 1.1238 | 1.0610 | 49 |
| 1.1246 | 1.0234 | 50 |
| 1.0971 | 0.9865 | 51 |
| 1.0883 | 1.0568 | 52 |
| 1.0774 | 1.0099 | 53 |
| 1.0581 | 1.0023 | 54 |
| 1.0680 | 1.0197 | 55 |
| 1.0682 | 0.9835 | 56 |
| 1.0390 | 0.9789 | 57 |
| 1.0480 | 1.0217 | 58 |
| 1.0273 | 0.9622 | 59 |
| 1.0062 | 1.0174 | 60 |
| 1.0088 | 0.9612 | 61 |
| 0.9909 | 0.9998 | 62 |
| 0.9821 | 1.0115 | 63 |
| 0.9752 | 0.9712 | 64 |
| 0.9816 | 0.9677 | 65 |
| 0.9569 | 0.9503 | 66 |
| 0.9521 | 1.0052 | 67 |
| 0.9384 | 0.9752 | 68 |
| 0.9468 | 0.9767 | 69 |
| 0.9241 | 1.0076 | 70 |
| 0.9211 | 0.9414 | 71 |
| 0.9166 | 1.0294 | 72 |
| 0.9044 | 0.9772 | 73 |
| 0.9025 | 0.9273 | 74 |
| 0.8909 | 1.0077 | 75 |
| 0.8831 | 0.9292 | 76 |
| 0.8702 | 0.9320 | 77 |
| 0.8644 | 0.9879 | 78 |
| 0.8599 | 0.9027 | 79 |
| 0.8434 | 0.9197 | 80 |
| 0.8561 | 0.9447 | 81 |
| 0.8330 | 0.9730 | 82 |
| 0.8328 | 0.9137 | 83 |
| 0.8221 | 0.9232 | 84 |
| 0.8166 | 0.9115 | 85 |
| 0.8025 | 0.9530 | 86 |
| 0.8070 | 0.9270 | 87 |
| 0.7968 | 0.8474 | 88 |
| 0.7880 | 0.9171 | 89 |
| 0.7834 | 0.8668 | 90 |
| 0.7786 | 0.9049 | 91 |
| 0.7595 | 0.9348 | 92 |
| 0.7573 | 0.8826 | 93 |
| 0.7505 | 0.8765 | 94 |
| 0.7474 | 0.9312 | 95 |
| 0.7386 | 0.9211 | 96 |
| 0.7490 | 0.9223 | 97 |
| 0.7214 | 0.8747 | 98 |
### Framework versions
- Transformers 4.18.0
- TensorFlow 2.8.0
- Datasets 2.2.1
- Tokenizers 0.12.1
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