File size: 22,417 Bytes
ae60221 |
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 |
---
library_name: transformers
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: ArabicNewSplits7_OSS_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k6_task1_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. -->
# ArabicNewSplits7_OSS_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k6_task1_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: 0.6526
- Qwk: 0.7429
- Mse: 0.6526
- Rmse: 0.8079
## 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 | 0.0444 | 2 | 6.6114 | 0.0123 | 6.6114 | 2.5713 |
| No log | 0.0889 | 4 | 4.4043 | 0.0732 | 4.4043 | 2.0986 |
| No log | 0.1333 | 6 | 2.8803 | 0.0952 | 2.8803 | 1.6971 |
| No log | 0.1778 | 8 | 2.4508 | 0.0284 | 2.4508 | 1.5655 |
| No log | 0.2222 | 10 | 2.0040 | 0.2143 | 2.0040 | 1.4156 |
| No log | 0.2667 | 12 | 1.7093 | 0.1667 | 1.7093 | 1.3074 |
| No log | 0.3111 | 14 | 1.6180 | 0.1869 | 1.6180 | 1.2720 |
| No log | 0.3556 | 16 | 1.4972 | 0.1698 | 1.4972 | 1.2236 |
| No log | 0.4 | 18 | 1.3365 | 0.2545 | 1.3365 | 1.1561 |
| No log | 0.4444 | 20 | 1.4337 | 0.3511 | 1.4337 | 1.1974 |
| No log | 0.4889 | 22 | 1.9006 | 0.3709 | 1.9006 | 1.3786 |
| No log | 0.5333 | 24 | 1.7709 | 0.4027 | 1.7709 | 1.3308 |
| No log | 0.5778 | 26 | 1.0056 | 0.6015 | 1.0056 | 1.0028 |
| No log | 0.6222 | 28 | 0.9092 | 0.6917 | 0.9092 | 0.9535 |
| No log | 0.6667 | 30 | 1.1067 | 0.6222 | 1.1067 | 1.0520 |
| No log | 0.7111 | 32 | 0.8426 | 0.7206 | 0.8426 | 0.9179 |
| No log | 0.7556 | 34 | 0.8974 | 0.6176 | 0.8974 | 0.9473 |
| No log | 0.8 | 36 | 0.9845 | 0.6216 | 0.9845 | 0.9922 |
| No log | 0.8444 | 38 | 1.2358 | 0.6265 | 1.2358 | 1.1116 |
| No log | 0.8889 | 40 | 0.8465 | 0.7262 | 0.8465 | 0.9201 |
| No log | 0.9333 | 42 | 0.5996 | 0.7950 | 0.5996 | 0.7743 |
| No log | 0.9778 | 44 | 0.5743 | 0.7898 | 0.5743 | 0.7578 |
| No log | 1.0222 | 46 | 0.7228 | 0.7561 | 0.7228 | 0.8502 |
| No log | 1.0667 | 48 | 1.6150 | 0.4859 | 1.6150 | 1.2708 |
| No log | 1.1111 | 50 | 1.9330 | 0.4565 | 1.9330 | 1.3903 |
| No log | 1.1556 | 52 | 1.2424 | 0.6092 | 1.2424 | 1.1146 |
| No log | 1.2 | 54 | 0.6106 | 0.7953 | 0.6106 | 0.7814 |
| No log | 1.2444 | 56 | 0.7013 | 0.7632 | 0.7013 | 0.8374 |
| No log | 1.2889 | 58 | 0.6970 | 0.7273 | 0.6970 | 0.8349 |
| No log | 1.3333 | 60 | 0.6694 | 0.75 | 0.6694 | 0.8182 |
| No log | 1.3778 | 62 | 0.6057 | 0.7347 | 0.6057 | 0.7783 |
| No log | 1.4222 | 64 | 0.6522 | 0.76 | 0.6522 | 0.8076 |
| No log | 1.4667 | 66 | 0.6435 | 0.7310 | 0.6435 | 0.8022 |
| No log | 1.5111 | 68 | 0.7914 | 0.6842 | 0.7914 | 0.8896 |
| No log | 1.5556 | 70 | 0.6505 | 0.7843 | 0.6505 | 0.8065 |
| No log | 1.6 | 72 | 0.6023 | 0.7692 | 0.6023 | 0.7761 |
| No log | 1.6444 | 74 | 0.5897 | 0.75 | 0.5897 | 0.7679 |
| No log | 1.6889 | 76 | 0.5682 | 0.75 | 0.5682 | 0.7538 |
| No log | 1.7333 | 78 | 0.6418 | 0.7821 | 0.6418 | 0.8011 |
| No log | 1.7778 | 80 | 0.7812 | 0.7665 | 0.7812 | 0.8839 |
| No log | 1.8222 | 82 | 0.7934 | 0.7746 | 0.7934 | 0.8907 |
| No log | 1.8667 | 84 | 0.6417 | 0.7636 | 0.6417 | 0.8011 |
| No log | 1.9111 | 86 | 0.5897 | 0.775 | 0.5897 | 0.7679 |
| No log | 1.9556 | 88 | 0.7395 | 0.7484 | 0.7395 | 0.8600 |
| No log | 2.0 | 90 | 0.8112 | 0.7368 | 0.8112 | 0.9007 |
| No log | 2.0444 | 92 | 0.7697 | 0.7248 | 0.7697 | 0.8773 |
| No log | 2.0889 | 94 | 0.7133 | 0.7368 | 0.7133 | 0.8445 |
| No log | 2.1333 | 96 | 0.7442 | 0.7484 | 0.7442 | 0.8627 |
| No log | 2.1778 | 98 | 0.7393 | 0.7531 | 0.7393 | 0.8598 |
| No log | 2.2222 | 100 | 0.6957 | 0.7816 | 0.6957 | 0.8341 |
| No log | 2.2667 | 102 | 0.7206 | 0.8020 | 0.7206 | 0.8489 |
| No log | 2.3111 | 104 | 0.6310 | 0.8023 | 0.6310 | 0.7944 |
| No log | 2.3556 | 106 | 0.6352 | 0.8144 | 0.6352 | 0.7970 |
| No log | 2.4 | 108 | 0.7417 | 0.7574 | 0.7417 | 0.8612 |
| No log | 2.4444 | 110 | 0.6060 | 0.7950 | 0.6060 | 0.7785 |
| No log | 2.4889 | 112 | 0.5565 | 0.8025 | 0.5565 | 0.7460 |
| No log | 2.5333 | 114 | 0.5538 | 0.7975 | 0.5538 | 0.7442 |
| No log | 2.5778 | 116 | 0.6619 | 0.7389 | 0.6619 | 0.8135 |
| No log | 2.6222 | 118 | 0.6718 | 0.75 | 0.6718 | 0.8196 |
| No log | 2.6667 | 120 | 0.5412 | 0.8075 | 0.5412 | 0.7357 |
| No log | 2.7111 | 122 | 0.5753 | 0.7853 | 0.5753 | 0.7585 |
| No log | 2.7556 | 124 | 0.6027 | 0.8144 | 0.6027 | 0.7763 |
| No log | 2.8 | 126 | 0.4854 | 0.8434 | 0.4854 | 0.6967 |
| No log | 2.8444 | 128 | 0.5949 | 0.7784 | 0.5949 | 0.7713 |
| No log | 2.8889 | 130 | 0.9325 | 0.7059 | 0.9325 | 0.9657 |
| No log | 2.9333 | 132 | 1.0228 | 0.7120 | 1.0228 | 1.0114 |
| No log | 2.9778 | 134 | 0.6469 | 0.7791 | 0.6469 | 0.8043 |
| No log | 3.0222 | 136 | 0.5702 | 0.8049 | 0.5702 | 0.7551 |
| No log | 3.0667 | 138 | 0.6165 | 0.7875 | 0.6165 | 0.7851 |
| No log | 3.1111 | 140 | 0.5653 | 0.8428 | 0.5653 | 0.7519 |
| No log | 3.1556 | 142 | 0.6222 | 0.7821 | 0.6222 | 0.7888 |
| No log | 3.2 | 144 | 0.6146 | 0.7712 | 0.6146 | 0.7839 |
| No log | 3.2444 | 146 | 0.5631 | 0.7949 | 0.5631 | 0.7504 |
| No log | 3.2889 | 148 | 0.5401 | 0.8333 | 0.5401 | 0.7349 |
| No log | 3.3333 | 150 | 0.5195 | 0.8409 | 0.5195 | 0.7208 |
| No log | 3.3778 | 152 | 0.5100 | 0.8306 | 0.5100 | 0.7142 |
| No log | 3.4222 | 154 | 0.5096 | 0.8434 | 0.5096 | 0.7139 |
| No log | 3.4667 | 156 | 0.5120 | 0.8304 | 0.5120 | 0.7155 |
| No log | 3.5111 | 158 | 0.5583 | 0.8187 | 0.5583 | 0.7472 |
| No log | 3.5556 | 160 | 0.6196 | 0.7826 | 0.6196 | 0.7872 |
| No log | 3.6 | 162 | 0.6098 | 0.7949 | 0.6098 | 0.7809 |
| No log | 3.6444 | 164 | 0.6061 | 0.8052 | 0.6061 | 0.7785 |
| No log | 3.6889 | 166 | 0.6081 | 0.8077 | 0.6081 | 0.7798 |
| No log | 3.7333 | 168 | 0.5628 | 0.8098 | 0.5628 | 0.7502 |
| No log | 3.7778 | 170 | 0.8343 | 0.7374 | 0.8343 | 0.9134 |
| No log | 3.8222 | 172 | 0.9469 | 0.6936 | 0.9469 | 0.9731 |
| No log | 3.8667 | 174 | 0.7277 | 0.6849 | 0.7277 | 0.8530 |
| No log | 3.9111 | 176 | 0.6042 | 0.8077 | 0.6042 | 0.7773 |
| No log | 3.9556 | 178 | 0.6312 | 0.7799 | 0.6312 | 0.7945 |
| No log | 4.0 | 180 | 0.5510 | 0.8025 | 0.5510 | 0.7423 |
| No log | 4.0444 | 182 | 0.5365 | 0.8380 | 0.5365 | 0.7325 |
| No log | 4.0889 | 184 | 0.6132 | 0.8187 | 0.6132 | 0.7831 |
| No log | 4.1333 | 186 | 0.5215 | 0.8525 | 0.5215 | 0.7222 |
| No log | 4.1778 | 188 | 0.5144 | 0.8492 | 0.5144 | 0.7173 |
| No log | 4.2222 | 190 | 0.5815 | 0.8177 | 0.5815 | 0.7625 |
| No log | 4.2667 | 192 | 0.5696 | 0.8177 | 0.5696 | 0.7547 |
| No log | 4.3111 | 194 | 0.5859 | 0.8068 | 0.5859 | 0.7654 |
| No log | 4.3556 | 196 | 0.5982 | 0.8024 | 0.5982 | 0.7734 |
| No log | 4.4 | 198 | 0.5708 | 0.8221 | 0.5708 | 0.7555 |
| No log | 4.4444 | 200 | 0.5794 | 0.8025 | 0.5794 | 0.7612 |
| No log | 4.4889 | 202 | 0.6168 | 0.7922 | 0.6168 | 0.7854 |
| No log | 4.5333 | 204 | 0.6735 | 0.76 | 0.6735 | 0.8207 |
| No log | 4.5778 | 206 | 0.6790 | 0.76 | 0.6790 | 0.8240 |
| No log | 4.6222 | 208 | 0.6946 | 0.7389 | 0.6946 | 0.8334 |
| No log | 4.6667 | 210 | 0.6741 | 0.7758 | 0.6741 | 0.8210 |
| No log | 4.7111 | 212 | 0.5764 | 0.8263 | 0.5764 | 0.7592 |
| No log | 4.7556 | 214 | 0.5793 | 0.8095 | 0.5793 | 0.7611 |
| No log | 4.8 | 216 | 0.5634 | 0.8193 | 0.5634 | 0.7506 |
| No log | 4.8444 | 218 | 0.5970 | 0.7758 | 0.5970 | 0.7727 |
| No log | 4.8889 | 220 | 0.6534 | 0.7578 | 0.6534 | 0.8083 |
| No log | 4.9333 | 222 | 0.6353 | 0.7468 | 0.6353 | 0.7970 |
| No log | 4.9778 | 224 | 0.5538 | 0.7792 | 0.5538 | 0.7442 |
| No log | 5.0222 | 226 | 0.5325 | 0.8344 | 0.5325 | 0.7297 |
| No log | 5.0667 | 228 | 0.5234 | 0.8272 | 0.5234 | 0.7235 |
| No log | 5.1111 | 230 | 0.5838 | 0.7950 | 0.5838 | 0.7640 |
| No log | 5.1556 | 232 | 0.6177 | 0.7875 | 0.6177 | 0.7859 |
| No log | 5.2 | 234 | 0.6114 | 0.7792 | 0.6114 | 0.7819 |
| No log | 5.2444 | 236 | 0.6375 | 0.7586 | 0.6375 | 0.7984 |
| No log | 5.2889 | 238 | 0.6570 | 0.7568 | 0.6570 | 0.8106 |
| No log | 5.3333 | 240 | 0.6343 | 0.7568 | 0.6343 | 0.7964 |
| No log | 5.3778 | 242 | 0.6049 | 0.7632 | 0.6049 | 0.7778 |
| No log | 5.4222 | 244 | 0.6262 | 0.7550 | 0.6262 | 0.7913 |
| No log | 5.4667 | 246 | 0.6235 | 0.7568 | 0.6235 | 0.7896 |
| No log | 5.5111 | 248 | 0.6353 | 0.7568 | 0.6353 | 0.7970 |
| No log | 5.5556 | 250 | 0.6581 | 0.7285 | 0.6581 | 0.8112 |
| No log | 5.6 | 252 | 0.6473 | 0.7172 | 0.6473 | 0.8046 |
| No log | 5.6444 | 254 | 0.6317 | 0.7413 | 0.6317 | 0.7948 |
| No log | 5.6889 | 256 | 0.6310 | 0.7286 | 0.6310 | 0.7944 |
| No log | 5.7333 | 258 | 0.6335 | 0.7571 | 0.6335 | 0.7959 |
| No log | 5.7778 | 260 | 0.6349 | 0.7286 | 0.6349 | 0.7968 |
| No log | 5.8222 | 262 | 0.6375 | 0.7324 | 0.6375 | 0.7984 |
| No log | 5.8667 | 264 | 0.7811 | 0.7237 | 0.7811 | 0.8838 |
| No log | 5.9111 | 266 | 0.8595 | 0.6982 | 0.8595 | 0.9271 |
| No log | 5.9556 | 268 | 0.6906 | 0.7237 | 0.6906 | 0.8310 |
| No log | 6.0 | 270 | 0.5657 | 0.8108 | 0.5657 | 0.7521 |
| No log | 6.0444 | 272 | 0.6042 | 0.7724 | 0.6042 | 0.7773 |
| No log | 6.0889 | 274 | 0.7426 | 0.7152 | 0.7426 | 0.8617 |
| No log | 6.1333 | 276 | 0.6104 | 0.7843 | 0.6104 | 0.7813 |
| No log | 6.1778 | 278 | 0.5099 | 0.8485 | 0.5099 | 0.7141 |
| No log | 6.2222 | 280 | 0.6144 | 0.8065 | 0.6144 | 0.7838 |
| No log | 6.2667 | 282 | 0.5796 | 0.8136 | 0.5796 | 0.7613 |
| No log | 6.3111 | 284 | 0.5364 | 0.8375 | 0.5364 | 0.7324 |
| No log | 6.3556 | 286 | 0.5674 | 0.8129 | 0.5674 | 0.7533 |
| No log | 6.4 | 288 | 0.6034 | 0.7843 | 0.6034 | 0.7768 |
| No log | 6.4444 | 290 | 0.6041 | 0.7974 | 0.6041 | 0.7773 |
| No log | 6.4889 | 292 | 0.6783 | 0.7114 | 0.6783 | 0.8236 |
| No log | 6.5333 | 294 | 0.8656 | 0.6957 | 0.8656 | 0.9304 |
| No log | 6.5778 | 296 | 0.9134 | 0.6533 | 0.9134 | 0.9557 |
| No log | 6.6222 | 298 | 0.8012 | 0.6475 | 0.8012 | 0.8951 |
| No log | 6.6667 | 300 | 0.7039 | 0.7338 | 0.7039 | 0.8390 |
| No log | 6.7111 | 302 | 0.6879 | 0.7568 | 0.6879 | 0.8294 |
| No log | 6.7556 | 304 | 0.7020 | 0.7417 | 0.7020 | 0.8379 |
| No log | 6.8 | 306 | 0.7252 | 0.7595 | 0.7252 | 0.8516 |
| No log | 6.8444 | 308 | 0.6971 | 0.7561 | 0.6971 | 0.8349 |
| No log | 6.8889 | 310 | 0.5765 | 0.7875 | 0.5765 | 0.7593 |
| No log | 6.9333 | 312 | 0.5433 | 0.8293 | 0.5433 | 0.7371 |
| No log | 6.9778 | 314 | 0.7664 | 0.75 | 0.7664 | 0.8755 |
| No log | 7.0222 | 316 | 0.8730 | 0.7253 | 0.8730 | 0.9344 |
| No log | 7.0667 | 318 | 0.7974 | 0.7226 | 0.7974 | 0.8930 |
| No log | 7.1111 | 320 | 0.6831 | 0.7552 | 0.6831 | 0.8265 |
| No log | 7.1556 | 322 | 0.6717 | 0.7552 | 0.6717 | 0.8196 |
| No log | 7.2 | 324 | 0.6482 | 0.7324 | 0.6482 | 0.8051 |
| No log | 7.2444 | 326 | 0.6234 | 0.75 | 0.6234 | 0.7896 |
| No log | 7.2889 | 328 | 0.6360 | 0.8 | 0.6360 | 0.7975 |
| No log | 7.3333 | 330 | 0.6000 | 0.8066 | 0.6000 | 0.7746 |
| No log | 7.3778 | 332 | 0.6453 | 0.7845 | 0.6453 | 0.8033 |
| No log | 7.4222 | 334 | 0.6075 | 0.7912 | 0.6075 | 0.7794 |
| No log | 7.4667 | 336 | 0.6057 | 0.7746 | 0.6057 | 0.7782 |
| No log | 7.5111 | 338 | 0.5724 | 0.7733 | 0.5724 | 0.7566 |
| No log | 7.5556 | 340 | 0.5803 | 0.7778 | 0.5803 | 0.7618 |
| No log | 7.6 | 342 | 0.6287 | 0.7286 | 0.6287 | 0.7929 |
| No log | 7.6444 | 344 | 0.6474 | 0.7606 | 0.6474 | 0.8046 |
| No log | 7.6889 | 346 | 0.6749 | 0.7234 | 0.6749 | 0.8215 |
| No log | 7.7333 | 348 | 0.6331 | 0.7361 | 0.6331 | 0.7957 |
| No log | 7.7778 | 350 | 0.5819 | 0.7891 | 0.5819 | 0.7628 |
| No log | 7.8222 | 352 | 0.5479 | 0.7843 | 0.5479 | 0.7402 |
| No log | 7.8667 | 354 | 0.5309 | 0.8263 | 0.5309 | 0.7286 |
| No log | 7.9111 | 356 | 0.5479 | 0.8052 | 0.5479 | 0.7402 |
| No log | 7.9556 | 358 | 0.5783 | 0.7763 | 0.5783 | 0.7605 |
| No log | 8.0 | 360 | 0.5649 | 0.7671 | 0.5649 | 0.7516 |
| No log | 8.0444 | 362 | 0.6276 | 0.7532 | 0.6276 | 0.7922 |
| No log | 8.0889 | 364 | 0.7619 | 0.7425 | 0.7619 | 0.8729 |
| No log | 8.1333 | 366 | 0.7498 | 0.7320 | 0.7498 | 0.8659 |
| No log | 8.1778 | 368 | 0.6637 | 0.7448 | 0.6637 | 0.8147 |
| No log | 8.2222 | 370 | 0.6423 | 0.7397 | 0.6423 | 0.8014 |
| No log | 8.2667 | 372 | 0.6098 | 0.7483 | 0.6098 | 0.7809 |
| No log | 8.3111 | 374 | 0.5812 | 0.8025 | 0.5812 | 0.7623 |
| No log | 8.3556 | 376 | 0.5601 | 0.8324 | 0.5601 | 0.7484 |
| No log | 8.4 | 378 | 0.5586 | 0.8304 | 0.5586 | 0.7474 |
| No log | 8.4444 | 380 | 0.5477 | 0.8171 | 0.5477 | 0.7401 |
| No log | 8.4889 | 382 | 0.5582 | 0.7922 | 0.5582 | 0.7471 |
| No log | 8.5333 | 384 | 0.5502 | 0.8000 | 0.5502 | 0.7417 |
| No log | 8.5778 | 386 | 0.5179 | 0.8503 | 0.5179 | 0.7197 |
| No log | 8.6222 | 388 | 0.5224 | 0.8208 | 0.5224 | 0.7228 |
| No log | 8.6667 | 390 | 0.5071 | 0.8492 | 0.5071 | 0.7121 |
| No log | 8.7111 | 392 | 0.5047 | 0.8523 | 0.5047 | 0.7104 |
| No log | 8.7556 | 394 | 0.4992 | 0.8492 | 0.4992 | 0.7065 |
| No log | 8.8 | 396 | 0.4897 | 0.8475 | 0.4897 | 0.6998 |
| No log | 8.8444 | 398 | 0.5070 | 0.8606 | 0.5070 | 0.7121 |
| No log | 8.8889 | 400 | 0.5536 | 0.7808 | 0.5536 | 0.7441 |
| No log | 8.9333 | 402 | 0.5909 | 0.7586 | 0.5909 | 0.7687 |
| No log | 8.9778 | 404 | 0.6079 | 0.7586 | 0.6079 | 0.7796 |
| No log | 9.0222 | 406 | 0.6305 | 0.75 | 0.6305 | 0.7940 |
| No log | 9.0667 | 408 | 0.6599 | 0.7222 | 0.6599 | 0.8123 |
| No log | 9.1111 | 410 | 0.6034 | 0.7586 | 0.6034 | 0.7768 |
| No log | 9.1556 | 412 | 0.6246 | 0.7947 | 0.6246 | 0.7903 |
| No log | 9.2 | 414 | 0.6614 | 0.76 | 0.6614 | 0.8133 |
| No log | 9.2444 | 416 | 0.6011 | 0.8105 | 0.6011 | 0.7753 |
| No log | 9.2889 | 418 | 0.6029 | 0.7517 | 0.6029 | 0.7765 |
| No log | 9.3333 | 420 | 0.8385 | 0.7219 | 0.8385 | 0.9157 |
| No log | 9.3778 | 422 | 1.0277 | 0.6705 | 1.0277 | 1.0137 |
| No log | 9.4222 | 424 | 0.9828 | 0.6216 | 0.9828 | 0.9914 |
| No log | 9.4667 | 426 | 0.8437 | 0.6853 | 0.8437 | 0.9185 |
| No log | 9.5111 | 428 | 0.6707 | 0.7324 | 0.6707 | 0.8190 |
| No log | 9.5556 | 430 | 0.6017 | 0.7361 | 0.6017 | 0.7757 |
| No log | 9.6 | 432 | 0.5792 | 0.7417 | 0.5792 | 0.7610 |
| No log | 9.6444 | 434 | 0.5700 | 0.7730 | 0.5700 | 0.7550 |
| No log | 9.6889 | 436 | 0.5775 | 0.7861 | 0.5775 | 0.7599 |
| No log | 9.7333 | 438 | 0.5584 | 0.7977 | 0.5584 | 0.7473 |
| No log | 9.7778 | 440 | 0.5143 | 0.8354 | 0.5143 | 0.7171 |
| No log | 9.8222 | 442 | 0.5308 | 0.8153 | 0.5308 | 0.7286 |
| No log | 9.8667 | 444 | 0.5678 | 0.8129 | 0.5678 | 0.7535 |
| No log | 9.9111 | 446 | 0.5905 | 0.7755 | 0.5905 | 0.7684 |
| No log | 9.9556 | 448 | 0.6385 | 0.7671 | 0.6385 | 0.7991 |
| No log | 10.0 | 450 | 0.6558 | 0.75 | 0.6558 | 0.8098 |
| No log | 10.0444 | 452 | 0.6559 | 0.7552 | 0.6559 | 0.8099 |
| No log | 10.0889 | 454 | 0.6374 | 0.7639 | 0.6374 | 0.7984 |
| No log | 10.1333 | 456 | 0.6132 | 0.7755 | 0.6132 | 0.7831 |
| No log | 10.1778 | 458 | 0.5976 | 0.7568 | 0.5976 | 0.7730 |
| No log | 10.2222 | 460 | 0.5756 | 0.7853 | 0.5756 | 0.7587 |
| No log | 10.2667 | 462 | 0.5710 | 0.7853 | 0.5710 | 0.7556 |
| No log | 10.3111 | 464 | 0.5776 | 0.7867 | 0.5776 | 0.7600 |
| No log | 10.3556 | 466 | 0.6501 | 0.7361 | 0.6501 | 0.8063 |
| No log | 10.4 | 468 | 0.7655 | 0.7042 | 0.7655 | 0.8749 |
| No log | 10.4444 | 470 | 0.8029 | 0.6957 | 0.8029 | 0.8961 |
| No log | 10.4889 | 472 | 0.7443 | 0.7234 | 0.7443 | 0.8627 |
| No log | 10.5333 | 474 | 0.6264 | 0.7413 | 0.6264 | 0.7915 |
| No log | 10.5778 | 476 | 0.5276 | 0.8289 | 0.5276 | 0.7264 |
| No log | 10.6222 | 478 | 0.4788 | 0.8375 | 0.4788 | 0.6920 |
| No log | 10.6667 | 480 | 0.4495 | 0.8721 | 0.4495 | 0.6704 |
| No log | 10.7111 | 482 | 0.4472 | 0.8686 | 0.4472 | 0.6688 |
| No log | 10.7556 | 484 | 0.4392 | 0.8621 | 0.4392 | 0.6627 |
| No log | 10.8 | 486 | 0.4495 | 0.8655 | 0.4495 | 0.6705 |
| No log | 10.8444 | 488 | 0.4826 | 0.8553 | 0.4826 | 0.6947 |
| No log | 10.8889 | 490 | 0.5865 | 0.7484 | 0.5865 | 0.7659 |
| No log | 10.9333 | 492 | 0.6696 | 0.7403 | 0.6696 | 0.8183 |
| No log | 10.9778 | 494 | 0.6510 | 0.7248 | 0.6510 | 0.8068 |
| No log | 11.0222 | 496 | 0.6093 | 0.7862 | 0.6093 | 0.7806 |
| No log | 11.0667 | 498 | 0.5671 | 0.8056 | 0.5671 | 0.7531 |
| 0.365 | 11.1111 | 500 | 0.5384 | 0.8138 | 0.5384 | 0.7338 |
| 0.365 | 11.1556 | 502 | 0.5049 | 0.8289 | 0.5049 | 0.7106 |
| 0.365 | 11.2 | 504 | 0.4819 | 0.8642 | 0.4819 | 0.6942 |
| 0.365 | 11.2444 | 506 | 0.4799 | 0.8554 | 0.4799 | 0.6928 |
| 0.365 | 11.2889 | 508 | 0.4839 | 0.8503 | 0.4839 | 0.6957 |
| 0.365 | 11.3333 | 510 | 0.4889 | 0.8415 | 0.4889 | 0.6992 |
| 0.365 | 11.3778 | 512 | 0.5011 | 0.8375 | 0.5011 | 0.7079 |
| 0.365 | 11.4222 | 514 | 0.5409 | 0.7758 | 0.5409 | 0.7355 |
| 0.365 | 11.4667 | 516 | 0.5545 | 0.7448 | 0.5545 | 0.7447 |
| 0.365 | 11.5111 | 518 | 0.6007 | 0.7413 | 0.6007 | 0.7751 |
| 0.365 | 11.5556 | 520 | 0.6531 | 0.7518 | 0.6531 | 0.8081 |
| 0.365 | 11.6 | 522 | 0.6526 | 0.7429 | 0.6526 | 0.8079 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
|