File size: 22,715 Bytes
06e10c5 e26a2fd 06e10c5 e26a2fd 06e10c5 e26a2fd 06e10c5 e26a2fd 06e10c5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 |
---
library_name: transformers
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: ArabicNewSplits8_usingALLEssays_FineTuningAraBERT_run2_AugV5_k15_task2_organization
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ArabicNewSplits8_usingALLEssays_FineTuningAraBERT_run2_AugV5_k15_task2_organization
This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5649
- Qwk: 0.5219
- Mse: 0.5649
- Rmse: 0.7516
## 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:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
|:-------------:|:------:|:----:|:---------------:|:-------:|:------:|:------:|
| No log | 0.0256 | 2 | 4.2562 | -0.0228 | 4.2562 | 2.0630 |
| No log | 0.0513 | 4 | 2.4534 | 0.0546 | 2.4534 | 1.5663 |
| No log | 0.0769 | 6 | 1.3931 | -0.0286 | 1.3931 | 1.1803 |
| No log | 0.1026 | 8 | 1.0970 | -0.0035 | 1.0970 | 1.0474 |
| No log | 0.1282 | 10 | 0.9665 | -0.0533 | 0.9665 | 0.9831 |
| No log | 0.1538 | 12 | 0.8994 | 0.0334 | 0.8994 | 0.9484 |
| No log | 0.1795 | 14 | 0.8133 | 0.2752 | 0.8133 | 0.9018 |
| No log | 0.2051 | 16 | 0.8587 | 0.1429 | 0.8587 | 0.9267 |
| No log | 0.2308 | 18 | 1.0442 | 0.1909 | 1.0442 | 1.0219 |
| No log | 0.2564 | 20 | 0.9528 | 0.2550 | 0.9528 | 0.9761 |
| No log | 0.2821 | 22 | 0.9216 | 0.2427 | 0.9216 | 0.9600 |
| No log | 0.3077 | 24 | 0.8479 | 0.2453 | 0.8479 | 0.9208 |
| No log | 0.3333 | 26 | 0.9169 | 0.3036 | 0.9169 | 0.9576 |
| No log | 0.3590 | 28 | 1.1156 | 0.2122 | 1.1156 | 1.0562 |
| No log | 0.3846 | 30 | 0.9887 | 0.2653 | 0.9887 | 0.9943 |
| No log | 0.4103 | 32 | 0.6573 | 0.3874 | 0.6573 | 0.8107 |
| No log | 0.4359 | 34 | 0.6120 | 0.4395 | 0.6120 | 0.7823 |
| No log | 0.4615 | 36 | 0.6180 | 0.4952 | 0.6180 | 0.7862 |
| No log | 0.4872 | 38 | 0.8359 | 0.3179 | 0.8359 | 0.9143 |
| No log | 0.5128 | 40 | 0.9573 | 0.2316 | 0.9573 | 0.9784 |
| No log | 0.5385 | 42 | 0.8576 | 0.2608 | 0.8576 | 0.9261 |
| No log | 0.5641 | 44 | 0.6280 | 0.4638 | 0.6280 | 0.7925 |
| No log | 0.5897 | 46 | 0.5706 | 0.5113 | 0.5706 | 0.7554 |
| No log | 0.6154 | 48 | 0.5597 | 0.4412 | 0.5597 | 0.7482 |
| No log | 0.6410 | 50 | 0.5657 | 0.4976 | 0.5657 | 0.7521 |
| No log | 0.6667 | 52 | 0.6493 | 0.4970 | 0.6493 | 0.8058 |
| No log | 0.6923 | 54 | 0.7677 | 0.4436 | 0.7677 | 0.8762 |
| No log | 0.7179 | 56 | 1.0950 | 0.3620 | 1.0950 | 1.0464 |
| No log | 0.7436 | 58 | 1.4397 | 0.2308 | 1.4397 | 1.1999 |
| No log | 0.7692 | 60 | 1.4453 | 0.2273 | 1.4453 | 1.2022 |
| No log | 0.7949 | 62 | 0.9801 | 0.3602 | 0.9801 | 0.9900 |
| No log | 0.8205 | 64 | 0.6088 | 0.5865 | 0.6088 | 0.7802 |
| No log | 0.8462 | 66 | 0.5652 | 0.5656 | 0.5652 | 0.7518 |
| No log | 0.8718 | 68 | 0.5720 | 0.5366 | 0.5720 | 0.7563 |
| No log | 0.8974 | 70 | 0.7298 | 0.4055 | 0.7298 | 0.8543 |
| No log | 0.9231 | 72 | 1.0653 | 0.3314 | 1.0653 | 1.0321 |
| No log | 0.9487 | 74 | 1.5102 | 0.2869 | 1.5102 | 1.2289 |
| No log | 0.9744 | 76 | 1.4053 | 0.3060 | 1.4053 | 1.1854 |
| No log | 1.0 | 78 | 0.9596 | 0.3917 | 0.9596 | 0.9796 |
| No log | 1.0256 | 80 | 0.8336 | 0.4300 | 0.8336 | 0.9130 |
| No log | 1.0513 | 82 | 0.6224 | 0.5815 | 0.6224 | 0.7889 |
| No log | 1.0769 | 84 | 0.5716 | 0.6212 | 0.5716 | 0.7560 |
| No log | 1.1026 | 86 | 0.5974 | 0.5611 | 0.5974 | 0.7729 |
| No log | 1.1282 | 88 | 0.8222 | 0.4622 | 0.8222 | 0.9067 |
| No log | 1.1538 | 90 | 0.9809 | 0.4040 | 0.9809 | 0.9904 |
| No log | 1.1795 | 92 | 0.8222 | 0.4921 | 0.8222 | 0.9067 |
| No log | 1.2051 | 94 | 0.7021 | 0.5077 | 0.7021 | 0.8379 |
| No log | 1.2308 | 96 | 0.6900 | 0.5351 | 0.6900 | 0.8307 |
| No log | 1.2564 | 98 | 0.6177 | 0.5311 | 0.6177 | 0.7859 |
| No log | 1.2821 | 100 | 0.6234 | 0.5079 | 0.6234 | 0.7895 |
| No log | 1.3077 | 102 | 0.6180 | 0.4946 | 0.6180 | 0.7861 |
| No log | 1.3333 | 104 | 0.6005 | 0.5290 | 0.6005 | 0.7749 |
| No log | 1.3590 | 106 | 0.6002 | 0.5222 | 0.6002 | 0.7748 |
| No log | 1.3846 | 108 | 0.6012 | 0.5427 | 0.6012 | 0.7754 |
| No log | 1.4103 | 110 | 0.6218 | 0.5402 | 0.6218 | 0.7885 |
| No log | 1.4359 | 112 | 0.6959 | 0.5329 | 0.6959 | 0.8342 |
| No log | 1.4615 | 114 | 0.8679 | 0.4418 | 0.8679 | 0.9316 |
| No log | 1.4872 | 116 | 0.7705 | 0.4654 | 0.7705 | 0.8778 |
| No log | 1.5128 | 118 | 0.6466 | 0.5614 | 0.6466 | 0.8041 |
| No log | 1.5385 | 120 | 0.6694 | 0.5419 | 0.6694 | 0.8182 |
| No log | 1.5641 | 122 | 0.8271 | 0.4841 | 0.8271 | 0.9095 |
| No log | 1.5897 | 124 | 0.8093 | 0.4604 | 0.8093 | 0.8996 |
| No log | 1.6154 | 126 | 0.6081 | 0.5549 | 0.6081 | 0.7798 |
| No log | 1.6410 | 128 | 0.5962 | 0.4893 | 0.5962 | 0.7721 |
| No log | 1.6667 | 130 | 0.5879 | 0.4685 | 0.5879 | 0.7667 |
| No log | 1.6923 | 132 | 0.6315 | 0.5226 | 0.6315 | 0.7947 |
| No log | 1.7179 | 134 | 0.7860 | 0.5282 | 0.7860 | 0.8866 |
| No log | 1.7436 | 136 | 0.7858 | 0.5289 | 0.7858 | 0.8864 |
| No log | 1.7692 | 138 | 0.6306 | 0.5173 | 0.6306 | 0.7941 |
| No log | 1.7949 | 140 | 0.6443 | 0.5145 | 0.6443 | 0.8027 |
| No log | 1.8205 | 142 | 0.6170 | 0.4967 | 0.6170 | 0.7855 |
| No log | 1.8462 | 144 | 0.6041 | 0.5957 | 0.6041 | 0.7772 |
| No log | 1.8718 | 146 | 0.6984 | 0.5051 | 0.6984 | 0.8357 |
| No log | 1.8974 | 148 | 0.7338 | 0.4978 | 0.7338 | 0.8566 |
| No log | 1.9231 | 150 | 0.5973 | 0.5477 | 0.5973 | 0.7728 |
| No log | 1.9487 | 152 | 0.6373 | 0.4980 | 0.6373 | 0.7983 |
| No log | 1.9744 | 154 | 0.6516 | 0.4967 | 0.6516 | 0.8072 |
| No log | 2.0 | 156 | 0.5927 | 0.5488 | 0.5927 | 0.7699 |
| No log | 2.0256 | 158 | 0.7969 | 0.4741 | 0.7969 | 0.8927 |
| No log | 2.0513 | 160 | 0.8674 | 0.4349 | 0.8674 | 0.9313 |
| No log | 2.0769 | 162 | 0.7876 | 0.4483 | 0.7876 | 0.8874 |
| No log | 2.1026 | 164 | 0.7173 | 0.4591 | 0.7173 | 0.8469 |
| No log | 2.1282 | 166 | 0.6508 | 0.5735 | 0.6508 | 0.8067 |
| No log | 2.1538 | 168 | 0.7179 | 0.4840 | 0.7179 | 0.8473 |
| No log | 2.1795 | 170 | 0.7076 | 0.5033 | 0.7076 | 0.8412 |
| No log | 2.2051 | 172 | 0.6651 | 0.5575 | 0.6651 | 0.8155 |
| No log | 2.2308 | 174 | 0.5938 | 0.5889 | 0.5938 | 0.7706 |
| No log | 2.2564 | 176 | 0.5889 | 0.5489 | 0.5889 | 0.7674 |
| No log | 2.2821 | 178 | 0.6283 | 0.5090 | 0.6283 | 0.7926 |
| No log | 2.3077 | 180 | 0.7806 | 0.4742 | 0.7806 | 0.8835 |
| No log | 2.3333 | 182 | 0.7977 | 0.4757 | 0.7977 | 0.8931 |
| No log | 2.3590 | 184 | 0.6623 | 0.5530 | 0.6623 | 0.8138 |
| No log | 2.3846 | 186 | 0.6730 | 0.5332 | 0.6730 | 0.8203 |
| No log | 2.4103 | 188 | 0.6882 | 0.5556 | 0.6882 | 0.8296 |
| No log | 2.4359 | 190 | 0.6415 | 0.5728 | 0.6415 | 0.8009 |
| No log | 2.4615 | 192 | 0.6079 | 0.5207 | 0.6079 | 0.7797 |
| No log | 2.4872 | 194 | 0.5996 | 0.5093 | 0.5996 | 0.7744 |
| No log | 2.5128 | 196 | 0.5833 | 0.4960 | 0.5833 | 0.7637 |
| No log | 2.5385 | 198 | 0.5729 | 0.4752 | 0.5729 | 0.7569 |
| No log | 2.5641 | 200 | 0.6005 | 0.4916 | 0.6005 | 0.7749 |
| No log | 2.5897 | 202 | 0.5817 | 0.4628 | 0.5817 | 0.7627 |
| No log | 2.6154 | 204 | 0.6475 | 0.4215 | 0.6475 | 0.8047 |
| No log | 2.6410 | 206 | 0.7092 | 0.4295 | 0.7092 | 0.8421 |
| No log | 2.6667 | 208 | 0.6497 | 0.4065 | 0.6497 | 0.8060 |
| No log | 2.6923 | 210 | 0.5928 | 0.4891 | 0.5928 | 0.7699 |
| No log | 2.7179 | 212 | 0.6166 | 0.5161 | 0.6166 | 0.7852 |
| No log | 2.7436 | 214 | 0.6030 | 0.5155 | 0.6030 | 0.7766 |
| No log | 2.7692 | 216 | 0.5900 | 0.5337 | 0.5900 | 0.7681 |
| No log | 2.7949 | 218 | 0.5828 | 0.5186 | 0.5828 | 0.7634 |
| No log | 2.8205 | 220 | 0.5796 | 0.5143 | 0.5796 | 0.7613 |
| No log | 2.8462 | 222 | 0.5823 | 0.5442 | 0.5823 | 0.7631 |
| No log | 2.8718 | 224 | 0.6295 | 0.5923 | 0.6295 | 0.7934 |
| No log | 2.8974 | 226 | 0.5893 | 0.6174 | 0.5893 | 0.7677 |
| No log | 2.9231 | 228 | 0.5650 | 0.5304 | 0.5650 | 0.7516 |
| No log | 2.9487 | 230 | 0.6264 | 0.4986 | 0.6264 | 0.7915 |
| No log | 2.9744 | 232 | 0.6210 | 0.4677 | 0.6210 | 0.7880 |
| No log | 3.0 | 234 | 0.5645 | 0.5139 | 0.5645 | 0.7514 |
| No log | 3.0256 | 236 | 0.5831 | 0.5214 | 0.5831 | 0.7636 |
| No log | 3.0513 | 238 | 0.5880 | 0.5205 | 0.5880 | 0.7668 |
| No log | 3.0769 | 240 | 0.5802 | 0.5455 | 0.5802 | 0.7617 |
| No log | 3.1026 | 242 | 0.5613 | 0.4745 | 0.5613 | 0.7492 |
| No log | 3.1282 | 244 | 0.5723 | 0.4835 | 0.5723 | 0.7565 |
| No log | 3.1538 | 246 | 0.5831 | 0.5173 | 0.5831 | 0.7636 |
| No log | 3.1795 | 248 | 0.6274 | 0.5392 | 0.6274 | 0.7921 |
| No log | 3.2051 | 250 | 0.6151 | 0.5009 | 0.6151 | 0.7843 |
| No log | 3.2308 | 252 | 0.6020 | 0.4915 | 0.6020 | 0.7759 |
| No log | 3.2564 | 254 | 0.5839 | 0.4978 | 0.5839 | 0.7641 |
| No log | 3.2821 | 256 | 0.5728 | 0.4788 | 0.5728 | 0.7568 |
| No log | 3.3077 | 258 | 0.6240 | 0.5600 | 0.6240 | 0.7900 |
| No log | 3.3333 | 260 | 0.6958 | 0.5493 | 0.6958 | 0.8341 |
| No log | 3.3590 | 262 | 0.6276 | 0.5152 | 0.6276 | 0.7922 |
| No log | 3.3846 | 264 | 0.5665 | 0.5256 | 0.5665 | 0.7526 |
| No log | 3.4103 | 266 | 0.5821 | 0.5049 | 0.5821 | 0.7629 |
| No log | 3.4359 | 268 | 0.5812 | 0.5064 | 0.5812 | 0.7624 |
| No log | 3.4615 | 270 | 0.5693 | 0.4725 | 0.5693 | 0.7546 |
| No log | 3.4872 | 272 | 0.5594 | 0.4616 | 0.5594 | 0.7479 |
| No log | 3.5128 | 274 | 0.6301 | 0.5096 | 0.6301 | 0.7938 |
| No log | 3.5385 | 276 | 0.7005 | 0.5228 | 0.7005 | 0.8369 |
| No log | 3.5641 | 278 | 0.6509 | 0.5249 | 0.6509 | 0.8068 |
| No log | 3.5897 | 280 | 0.6408 | 0.4834 | 0.6408 | 0.8005 |
| No log | 3.6154 | 282 | 0.6640 | 0.4577 | 0.6640 | 0.8148 |
| No log | 3.6410 | 284 | 0.6362 | 0.4534 | 0.6362 | 0.7976 |
| No log | 3.6667 | 286 | 0.6263 | 0.4705 | 0.6263 | 0.7914 |
| No log | 3.6923 | 288 | 0.6821 | 0.5066 | 0.6821 | 0.8259 |
| No log | 3.7179 | 290 | 0.7795 | 0.4913 | 0.7795 | 0.8829 |
| No log | 3.7436 | 292 | 0.7041 | 0.4989 | 0.7041 | 0.8391 |
| No log | 3.7692 | 294 | 0.6211 | 0.4458 | 0.6211 | 0.7881 |
| No log | 3.7949 | 296 | 0.6031 | 0.4273 | 0.6031 | 0.7766 |
| No log | 3.8205 | 298 | 0.6041 | 0.4099 | 0.6041 | 0.7772 |
| No log | 3.8462 | 300 | 0.6017 | 0.4744 | 0.6017 | 0.7757 |
| No log | 3.8718 | 302 | 0.6825 | 0.4920 | 0.6825 | 0.8261 |
| No log | 3.8974 | 304 | 0.7542 | 0.4571 | 0.7542 | 0.8685 |
| No log | 3.9231 | 306 | 0.6713 | 0.5600 | 0.6713 | 0.8193 |
| No log | 3.9487 | 308 | 0.6428 | 0.4932 | 0.6428 | 0.8017 |
| No log | 3.9744 | 310 | 0.6855 | 0.4513 | 0.6855 | 0.8279 |
| No log | 4.0 | 312 | 0.6746 | 0.4548 | 0.6746 | 0.8214 |
| No log | 4.0256 | 314 | 0.6114 | 0.5150 | 0.6114 | 0.7819 |
| No log | 4.0513 | 316 | 0.5740 | 0.5536 | 0.5740 | 0.7577 |
| No log | 4.0769 | 318 | 0.6215 | 0.5095 | 0.6215 | 0.7884 |
| No log | 4.1026 | 320 | 0.6555 | 0.5508 | 0.6555 | 0.8096 |
| No log | 4.1282 | 322 | 0.6226 | 0.5575 | 0.6226 | 0.7890 |
| No log | 4.1538 | 324 | 0.5925 | 0.5606 | 0.5925 | 0.7698 |
| No log | 4.1795 | 326 | 0.5767 | 0.5426 | 0.5767 | 0.7594 |
| No log | 4.2051 | 328 | 0.5777 | 0.5850 | 0.5777 | 0.7601 |
| No log | 4.2308 | 330 | 0.5895 | 0.5098 | 0.5895 | 0.7678 |
| No log | 4.2564 | 332 | 0.5804 | 0.4661 | 0.5804 | 0.7618 |
| No log | 4.2821 | 334 | 0.5666 | 0.5122 | 0.5666 | 0.7527 |
| No log | 4.3077 | 336 | 0.5699 | 0.5807 | 0.5699 | 0.7549 |
| No log | 4.3333 | 338 | 0.5971 | 0.4884 | 0.5971 | 0.7727 |
| No log | 4.3590 | 340 | 0.6149 | 0.4913 | 0.6149 | 0.7842 |
| No log | 4.3846 | 342 | 0.6337 | 0.5065 | 0.6337 | 0.7960 |
| No log | 4.4103 | 344 | 0.6217 | 0.4943 | 0.6217 | 0.7885 |
| No log | 4.4359 | 346 | 0.5890 | 0.5884 | 0.5890 | 0.7675 |
| No log | 4.4615 | 348 | 0.5757 | 0.5634 | 0.5757 | 0.7587 |
| No log | 4.4872 | 350 | 0.5661 | 0.5484 | 0.5661 | 0.7524 |
| No log | 4.5128 | 352 | 0.5696 | 0.5378 | 0.5696 | 0.7547 |
| No log | 4.5385 | 354 | 0.5679 | 0.5248 | 0.5679 | 0.7536 |
| No log | 4.5641 | 356 | 0.5799 | 0.4992 | 0.5799 | 0.7615 |
| No log | 4.5897 | 358 | 0.5778 | 0.4746 | 0.5778 | 0.7601 |
| No log | 4.6154 | 360 | 0.5701 | 0.4623 | 0.5701 | 0.7551 |
| No log | 4.6410 | 362 | 0.5939 | 0.4758 | 0.5939 | 0.7706 |
| No log | 4.6667 | 364 | 0.5820 | 0.5414 | 0.5820 | 0.7629 |
| No log | 4.6923 | 366 | 0.5740 | 0.5432 | 0.5740 | 0.7577 |
| No log | 4.7179 | 368 | 0.5725 | 0.5505 | 0.5725 | 0.7566 |
| No log | 4.7436 | 370 | 0.5630 | 0.5454 | 0.5630 | 0.7504 |
| No log | 4.7692 | 372 | 0.5911 | 0.5395 | 0.5911 | 0.7688 |
| No log | 4.7949 | 374 | 0.5819 | 0.5110 | 0.5819 | 0.7628 |
| No log | 4.8205 | 376 | 0.5470 | 0.5017 | 0.5470 | 0.7396 |
| No log | 4.8462 | 378 | 0.5383 | 0.5024 | 0.5383 | 0.7337 |
| No log | 4.8718 | 380 | 0.5405 | 0.4859 | 0.5405 | 0.7352 |
| No log | 4.8974 | 382 | 0.5456 | 0.5172 | 0.5456 | 0.7386 |
| No log | 4.9231 | 384 | 0.5485 | 0.5352 | 0.5485 | 0.7406 |
| No log | 4.9487 | 386 | 0.5528 | 0.5381 | 0.5528 | 0.7435 |
| No log | 4.9744 | 388 | 0.5589 | 0.5441 | 0.5589 | 0.7476 |
| No log | 5.0 | 390 | 0.5570 | 0.4921 | 0.5570 | 0.7463 |
| No log | 5.0256 | 392 | 0.5565 | 0.4734 | 0.5565 | 0.7460 |
| No log | 5.0513 | 394 | 0.5328 | 0.5233 | 0.5328 | 0.7299 |
| No log | 5.0769 | 396 | 0.5553 | 0.5214 | 0.5553 | 0.7452 |
| No log | 5.1026 | 398 | 0.5520 | 0.5340 | 0.5520 | 0.7430 |
| No log | 5.1282 | 400 | 0.5539 | 0.5639 | 0.5539 | 0.7442 |
| No log | 5.1538 | 402 | 0.5602 | 0.5713 | 0.5602 | 0.7485 |
| No log | 5.1795 | 404 | 0.5429 | 0.5374 | 0.5429 | 0.7368 |
| No log | 5.2051 | 406 | 0.5281 | 0.5279 | 0.5281 | 0.7267 |
| No log | 5.2308 | 408 | 0.5342 | 0.5069 | 0.5342 | 0.7309 |
| No log | 5.2564 | 410 | 0.5531 | 0.5006 | 0.5531 | 0.7437 |
| No log | 5.2821 | 412 | 0.5551 | 0.5181 | 0.5551 | 0.7451 |
| No log | 5.3077 | 414 | 0.5507 | 0.5802 | 0.5507 | 0.7421 |
| No log | 5.3333 | 416 | 0.5530 | 0.5502 | 0.5530 | 0.7437 |
| No log | 5.3590 | 418 | 0.5795 | 0.5644 | 0.5795 | 0.7612 |
| No log | 5.3846 | 420 | 0.5834 | 0.5638 | 0.5834 | 0.7638 |
| No log | 5.4103 | 422 | 0.5839 | 0.5948 | 0.5839 | 0.7641 |
| No log | 5.4359 | 424 | 0.6288 | 0.5507 | 0.6288 | 0.7929 |
| No log | 5.4615 | 426 | 0.6519 | 0.5490 | 0.6519 | 0.8074 |
| No log | 5.4872 | 428 | 0.6016 | 0.5836 | 0.6016 | 0.7756 |
| No log | 5.5128 | 430 | 0.5811 | 0.5679 | 0.5811 | 0.7623 |
| No log | 5.5385 | 432 | 0.5627 | 0.5304 | 0.5627 | 0.7502 |
| No log | 5.5641 | 434 | 0.5501 | 0.4497 | 0.5501 | 0.7417 |
| No log | 5.5897 | 436 | 0.5616 | 0.4377 | 0.5616 | 0.7494 |
| No log | 5.6154 | 438 | 0.5747 | 0.4610 | 0.5747 | 0.7581 |
| No log | 5.6410 | 440 | 0.5972 | 0.4983 | 0.5972 | 0.7728 |
| No log | 5.6667 | 442 | 0.5820 | 0.4630 | 0.5820 | 0.7629 |
| No log | 5.6923 | 444 | 0.5616 | 0.5644 | 0.5616 | 0.7494 |
| No log | 5.7179 | 446 | 0.5885 | 0.5508 | 0.5885 | 0.7672 |
| No log | 5.7436 | 448 | 0.6100 | 0.5453 | 0.6100 | 0.7810 |
| No log | 5.7692 | 450 | 0.6061 | 0.5500 | 0.6061 | 0.7785 |
| No log | 5.7949 | 452 | 0.6516 | 0.5695 | 0.6516 | 0.8072 |
| No log | 5.8205 | 454 | 0.7034 | 0.5665 | 0.7034 | 0.8387 |
| No log | 5.8462 | 456 | 0.6714 | 0.5521 | 0.6714 | 0.8194 |
| No log | 5.8718 | 458 | 0.6152 | 0.5341 | 0.6152 | 0.7843 |
| No log | 5.8974 | 460 | 0.5997 | 0.5262 | 0.5997 | 0.7744 |
| No log | 5.9231 | 462 | 0.5956 | 0.5437 | 0.5956 | 0.7717 |
| No log | 5.9487 | 464 | 0.5725 | 0.5293 | 0.5725 | 0.7566 |
| No log | 5.9744 | 466 | 0.5925 | 0.5794 | 0.5925 | 0.7698 |
| No log | 6.0 | 468 | 0.6880 | 0.4996 | 0.6880 | 0.8294 |
| No log | 6.0256 | 470 | 0.7238 | 0.4811 | 0.7238 | 0.8508 |
| No log | 6.0513 | 472 | 0.7165 | 0.4996 | 0.7165 | 0.8465 |
| No log | 6.0769 | 474 | 0.6677 | 0.5205 | 0.6677 | 0.8172 |
| No log | 6.1026 | 476 | 0.6245 | 0.5772 | 0.6245 | 0.7902 |
| No log | 6.1282 | 478 | 0.6224 | 0.5651 | 0.6224 | 0.7889 |
| No log | 6.1538 | 480 | 0.6301 | 0.5672 | 0.6301 | 0.7938 |
| No log | 6.1795 | 482 | 0.6330 | 0.5672 | 0.6330 | 0.7956 |
| No log | 6.2051 | 484 | 0.6750 | 0.5337 | 0.6750 | 0.8216 |
| No log | 6.2308 | 486 | 0.6718 | 0.5518 | 0.6718 | 0.8197 |
| No log | 6.2564 | 488 | 0.6313 | 0.5633 | 0.6313 | 0.7945 |
| No log | 6.2821 | 490 | 0.6225 | 0.5074 | 0.6225 | 0.7890 |
| No log | 6.3077 | 492 | 0.6492 | 0.5420 | 0.6492 | 0.8057 |
| No log | 6.3333 | 494 | 0.6620 | 0.5425 | 0.6620 | 0.8136 |
| No log | 6.3590 | 496 | 0.6559 | 0.5675 | 0.6559 | 0.8099 |
| No log | 6.3846 | 498 | 0.6169 | 0.5558 | 0.6169 | 0.7854 |
| 0.3309 | 6.4103 | 500 | 0.5951 | 0.5676 | 0.5951 | 0.7714 |
| 0.3309 | 6.4359 | 502 | 0.5703 | 0.5757 | 0.5703 | 0.7552 |
| 0.3309 | 6.4615 | 504 | 0.5660 | 0.5318 | 0.5660 | 0.7523 |
| 0.3309 | 6.4872 | 506 | 0.5574 | 0.5499 | 0.5574 | 0.7466 |
| 0.3309 | 6.5128 | 508 | 0.5550 | 0.5402 | 0.5550 | 0.7450 |
| 0.3309 | 6.5385 | 510 | 0.5553 | 0.5735 | 0.5553 | 0.7452 |
| 0.3309 | 6.5641 | 512 | 0.5608 | 0.5917 | 0.5608 | 0.7488 |
| 0.3309 | 6.5897 | 514 | 0.5816 | 0.5534 | 0.5816 | 0.7626 |
| 0.3309 | 6.6154 | 516 | 0.6215 | 0.5462 | 0.6215 | 0.7883 |
| 0.3309 | 6.6410 | 518 | 0.6005 | 0.5525 | 0.6005 | 0.7749 |
| 0.3309 | 6.6667 | 520 | 0.5582 | 0.5778 | 0.5582 | 0.7471 |
| 0.3309 | 6.6923 | 522 | 0.5879 | 0.5098 | 0.5879 | 0.7668 |
| 0.3309 | 6.7179 | 524 | 0.6432 | 0.5072 | 0.6432 | 0.8020 |
| 0.3309 | 6.7436 | 526 | 0.6094 | 0.4867 | 0.6094 | 0.7806 |
| 0.3309 | 6.7692 | 528 | 0.5568 | 0.5471 | 0.5568 | 0.7462 |
| 0.3309 | 6.7949 | 530 | 0.5649 | 0.5219 | 0.5649 | 0.7516 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
|