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---
base_model: Malvegil/prologue_creator-model
tags:
- generated_from_keras_callback
model-index:
- name: Malvegil/prologue_creator-model
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. -->
# Malvegil/prologue_creator-model
This model is a fine-tuned version of [Malvegil/prologue_creator-model](https://huggingface.co/Malvegil/prologue_creator-model) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.8078
- Validation Loss: 5.6164
- Epoch: 235
## 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 |
|:----------:|:---------------:|:-----:|
| 9.6983 | 8.6325 | 0 |
| 7.5394 | 7.4380 | 1 |
| 6.8454 | 6.9855 | 2 |
| 6.5034 | 6.8347 | 3 |
| 6.3289 | 6.6883 | 4 |
| 6.1540 | 6.5173 | 5 |
| 6.0244 | 6.3997 | 6 |
| 5.9258 | 6.3245 | 7 |
| 5.8095 | 6.2648 | 8 |
| 5.7688 | 6.1865 | 9 |
| 5.6244 | 6.1095 | 10 |
| 5.5619 | 6.0552 | 11 |
| 5.4940 | 6.0000 | 12 |
| 5.3603 | 5.9456 | 13 |
| 5.2852 | 5.8861 | 14 |
| 5.2218 | 5.8256 | 15 |
| 5.1715 | 5.7722 | 16 |
| 5.0556 | 5.7236 | 17 |
| 5.0339 | 5.6669 | 18 |
| 4.8776 | 5.6155 | 19 |
| 4.9133 | 5.5683 | 20 |
| 4.8350 | 5.5166 | 21 |
| 4.6951 | 5.4712 | 22 |
| 4.7144 | 5.4447 | 23 |
| 4.6560 | 5.3954 | 24 |
| 4.6125 | 5.3449 | 25 |
| 4.5494 | 5.3382 | 26 |
| 4.3536 | 5.2989 | 27 |
| 4.3613 | 5.2537 | 28 |
| 4.3123 | 5.2269 | 29 |
| 4.2677 | 5.2115 | 30 |
| 4.2407 | 5.1566 | 31 |
| 4.1543 | 5.1413 | 32 |
| 4.0961 | 5.1284 | 33 |
| 4.0779 | 5.0771 | 34 |
| 4.0303 | 5.0722 | 35 |
| 3.9734 | 5.0550 | 36 |
| 3.9541 | 5.0060 | 37 |
| 3.9188 | 4.9941 | 38 |
| 3.8350 | 4.9851 | 39 |
| 3.8081 | 4.9648 | 40 |
| 3.7395 | 4.9533 | 41 |
| 3.7045 | 4.9112 | 42 |
| 3.6765 | 4.9185 | 43 |
| 3.5667 | 4.8981 | 44 |
| 3.5491 | 4.8510 | 45 |
| 3.5547 | 4.8688 | 46 |
| 3.5317 | 4.8393 | 47 |
| 3.4210 | 4.8366 | 48 |
| 3.4503 | 4.8120 | 49 |
| 3.4187 | 4.8045 | 50 |
| 3.3313 | 4.7899 | 51 |
| 3.2695 | 4.7733 | 52 |
| 3.2980 | 4.7643 | 53 |
| 3.2614 | 4.7592 | 54 |
| 3.2011 | 4.7353 | 55 |
| 3.1756 | 4.7323 | 56 |
| 3.1325 | 4.7405 | 57 |
| 3.1642 | 4.6849 | 58 |
| 3.0915 | 4.7039 | 59 |
| 3.0950 | 4.6905 | 60 |
| 2.9946 | 4.6777 | 61 |
| 3.0338 | 4.7064 | 62 |
| 2.9554 | 4.6617 | 63 |
| 2.9999 | 4.6723 | 64 |
| 2.9410 | 4.6397 | 65 |
| 2.9157 | 4.6493 | 66 |
| 2.8930 | 4.6641 | 67 |
| 2.8620 | 4.6019 | 68 |
| 2.8726 | 4.6564 | 69 |
| 2.8386 | 4.6286 | 70 |
| 2.8574 | 4.6259 | 71 |
| 2.8023 | 4.6359 | 72 |
| 2.7938 | 4.6031 | 73 |
| 2.7686 | 4.6159 | 74 |
| 2.7211 | 4.6128 | 75 |
| 2.6670 | 4.5913 | 76 |
| 2.6814 | 4.6226 | 77 |
| 2.6588 | 4.6188 | 78 |
| 2.6030 | 4.5964 | 79 |
| 2.6216 | 4.6019 | 80 |
| 2.5280 | 4.6018 | 81 |
| 2.5754 | 4.5851 | 82 |
| 2.5673 | 4.5901 | 83 |
| 2.5393 | 4.6256 | 84 |
| 2.4955 | 4.5802 | 85 |
| 2.4958 | 4.6054 | 86 |
| 2.5005 | 4.6039 | 87 |
| 2.4841 | 4.5920 | 88 |
| 2.4570 | 4.6012 | 89 |
| 2.4515 | 4.5890 | 90 |
| 2.4431 | 4.5838 | 91 |
| 2.3742 | 4.5787 | 92 |
| 2.3844 | 4.6137 | 93 |
| 2.3383 | 4.5567 | 94 |
| 2.3353 | 4.6001 | 95 |
| 2.3191 | 4.5930 | 96 |
| 2.3239 | 4.6078 | 97 |
| 2.2769 | 4.6426 | 98 |
| 2.3320 | 4.5895 | 99 |
| 2.2817 | 4.5816 | 100 |
| 2.2582 | 4.6319 | 101 |
| 2.1774 | 4.6308 | 102 |
| 2.2102 | 4.6072 | 103 |
| 2.1617 | 4.6217 | 104 |
| 2.1204 | 4.6111 | 105 |
| 2.1133 | 4.6397 | 106 |
| 2.1467 | 4.6421 | 107 |
| 2.1342 | 4.6318 | 108 |
| 2.1181 | 4.6555 | 109 |
| 2.0767 | 4.6562 | 110 |
| 2.0712 | 4.6533 | 111 |
| 2.0510 | 4.6722 | 112 |
| 2.0286 | 4.6437 | 113 |
| 2.0246 | 4.6431 | 114 |
| 2.0103 | 4.6450 | 115 |
| 2.0312 | 4.7080 | 116 |
| 2.0114 | 4.6146 | 117 |
| 1.9577 | 4.7103 | 118 |
| 1.9565 | 4.6865 | 119 |
| 1.9472 | 4.6602 | 120 |
| 1.9208 | 4.7423 | 121 |
| 1.8886 | 4.6638 | 122 |
| 1.9209 | 4.7388 | 123 |
| 1.8418 | 4.6900 | 124 |
| 1.8558 | 4.7059 | 125 |
| 1.8710 | 4.7353 | 126 |
| 1.8964 | 4.6955 | 127 |
| 1.8434 | 4.7402 | 128 |
| 1.8208 | 4.7557 | 129 |
| 1.8239 | 4.7254 | 130 |
| 1.8503 | 4.7575 | 131 |
| 1.7790 | 4.7725 | 132 |
| 1.7704 | 4.7971 | 133 |
| 1.7516 | 4.7445 | 134 |
| 1.7630 | 4.8046 | 135 |
| 1.7549 | 4.8150 | 136 |
| 1.7104 | 4.7884 | 137 |
| 1.6935 | 4.8472 | 138 |
| 1.6870 | 4.8170 | 139 |
| 1.6855 | 4.7915 | 140 |
| 1.6557 | 4.8719 | 141 |
| 1.6574 | 4.8336 | 142 |
| 1.5848 | 4.8889 | 143 |
| 1.6420 | 4.8585 | 144 |
| 1.6126 | 4.8700 | 145 |
| 1.5733 | 4.8807 | 146 |
| 1.5987 | 4.9093 | 147 |
| 1.5042 | 4.8983 | 148 |
| 1.5607 | 4.9012 | 149 |
| 1.5851 | 4.9208 | 150 |
| 1.5446 | 4.9047 | 151 |
| 1.5388 | 4.9215 | 152 |
| 1.5056 | 4.9796 | 153 |
| 1.5179 | 4.9090 | 154 |
| 1.4876 | 4.9935 | 155 |
| 1.4975 | 4.9810 | 156 |
| 1.4607 | 5.0071 | 157 |
| 1.5030 | 4.9251 | 158 |
| 1.4315 | 5.0219 | 159 |
| 1.4314 | 4.9997 | 160 |
| 1.4178 | 4.9675 | 161 |
| 1.4635 | 5.0669 | 162 |
| 1.4097 | 5.0152 | 163 |
| 1.4132 | 5.0367 | 164 |
| 1.3775 | 5.0395 | 165 |
| 1.4041 | 5.0492 | 166 |
| 1.3943 | 5.0470 | 167 |
| 1.3495 | 5.1050 | 168 |
| 1.3552 | 5.1041 | 169 |
| 1.3615 | 5.0648 | 170 |
| 1.3254 | 5.1234 | 171 |
| 1.3445 | 5.0723 | 172 |
| 1.3316 | 5.1059 | 173 |
| 1.3324 | 5.1294 | 174 |
| 1.2835 | 5.1263 | 175 |
| 1.2682 | 5.1415 | 176 |
| 1.2784 | 5.0970 | 177 |
| 1.2765 | 5.1549 | 178 |
| 1.2319 | 5.1690 | 179 |
| 1.2499 | 5.1262 | 180 |
| 1.1930 | 5.2097 | 181 |
| 1.1929 | 5.1751 | 182 |
| 1.2155 | 5.1879 | 183 |
| 1.1793 | 5.2163 | 184 |
| 1.2233 | 5.2055 | 185 |
| 1.1913 | 5.2115 | 186 |
| 1.1525 | 5.2521 | 187 |
| 1.1655 | 5.2302 | 188 |
| 1.1481 | 5.2551 | 189 |
| 1.1580 | 5.2635 | 190 |
| 1.1389 | 5.2528 | 191 |
| 1.1284 | 5.2694 | 192 |
| 1.1326 | 5.2906 | 193 |
| 1.1092 | 5.2957 | 194 |
| 1.0763 | 5.3227 | 195 |
| 1.0933 | 5.3446 | 196 |
| 1.0921 | 5.3191 | 197 |
| 1.0771 | 5.3399 | 198 |
| 1.0682 | 5.3906 | 199 |
| 1.0679 | 5.3286 | 200 |
| 1.0526 | 5.3256 | 201 |
| 1.0728 | 5.3739 | 202 |
| 1.0440 | 5.3422 | 203 |
| 1.0250 | 5.3946 | 204 |
| 1.0444 | 5.3930 | 205 |
| 1.0013 | 5.4044 | 206 |
| 0.9885 | 5.4122 | 207 |
| 1.0002 | 5.4359 | 208 |
| 0.9855 | 5.4380 | 209 |
| 0.9918 | 5.4045 | 210 |
| 0.9711 | 5.4300 | 211 |
| 0.9513 | 5.4863 | 212 |
| 0.9615 | 5.4596 | 213 |
| 0.9264 | 5.4859 | 214 |
| 0.9255 | 5.4913 | 215 |
| 0.9387 | 5.4630 | 216 |
| 0.9216 | 5.4758 | 217 |
| 0.9157 | 5.4729 | 218 |
| 0.8907 | 5.5127 | 219 |
| 0.9049 | 5.5270 | 220 |
| 0.8869 | 5.5087 | 221 |
| 0.8787 | 5.5236 | 222 |
| 0.8839 | 5.5024 | 223 |
| 0.8711 | 5.5289 | 224 |
| 0.8663 | 5.5205 | 225 |
| 0.8504 | 5.5972 | 226 |
| 0.8532 | 5.5749 | 227 |
| 0.8397 | 5.5873 | 228 |
| 0.8358 | 5.5819 | 229 |
| 0.8230 | 5.5610 | 230 |
| 0.8384 | 5.5884 | 231 |
| 0.8251 | 5.5783 | 232 |
| 0.8137 | 5.5916 | 233 |
| 0.8078 | 5.6334 | 234 |
| 0.8078 | 5.6164 | 235 |
### Framework versions
- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1
|