File size: 19,326 Bytes
e6aea3a |
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 |
---
library_name: peft
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: base-lora
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. -->
# base-lora
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6392
- Rouge1: 7.4493
- Rouge2: 1.1542
- Rougel: 5.9231
- Rougelsum: 5.9247
## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 18.055 | 0.0203 | 5 | 11.6119 | 3.9124 | 0.4535 | 3.3358 | 3.3389 |
| 18.0636 | 0.0407 | 10 | 11.6017 | 3.9202 | 0.4545 | 3.3537 | 3.3567 |
| 18.9841 | 0.0610 | 15 | 11.5957 | 3.9219 | 0.4510 | 3.3520 | 3.3526 |
| 17.1948 | 0.0813 | 20 | 11.5334 | 3.9691 | 0.4539 | 3.3957 | 3.3985 |
| 17.9028 | 0.1016 | 25 | 11.4994 | 3.9721 | 0.4727 | 3.4036 | 3.4074 |
| 16.9331 | 0.1220 | 30 | 11.4228 | 3.9728 | 0.4712 | 3.4087 | 3.4104 |
| 19.6095 | 0.1423 | 35 | 11.3819 | 3.9596 | 0.4660 | 3.3891 | 3.3898 |
| 16.8935 | 0.1626 | 40 | 11.2556 | 3.9354 | 0.4682 | 3.3794 | 3.3839 |
| 16.3195 | 0.1829 | 45 | 11.2026 | 3.9342 | 0.4632 | 3.3706 | 3.3735 |
| 16.091 | 0.2033 | 50 | 11.1314 | 3.9621 | 0.4624 | 3.3697 | 3.3749 |
| 17.8748 | 0.2236 | 55 | 11.0424 | 4.0045 | 0.4748 | 3.4006 | 3.4093 |
| 16.3976 | 0.2439 | 60 | 10.8993 | 4.0416 | 0.4779 | 3.4208 | 3.4330 |
| 15.8952 | 0.2642 | 65 | 10.7943 | 4.0830 | 0.4840 | 3.4525 | 3.4582 |
| 16.3455 | 0.2846 | 70 | 10.6194 | 4.0705 | 0.4937 | 3.4405 | 3.4496 |
| 15.957 | 0.3049 | 75 | 10.4643 | 4.1590 | 0.4948 | 3.5013 | 3.5069 |
| 16.3171 | 0.3252 | 80 | 10.2894 | 4.1872 | 0.4886 | 3.5251 | 3.5294 |
| 14.3489 | 0.3455 | 85 | 10.1070 | 4.0644 | 0.4394 | 3.4238 | 3.4249 |
| 14.9094 | 0.3659 | 90 | 9.9338 | 4.0472 | 0.4433 | 3.4151 | 3.4233 |
| 15.1002 | 0.3862 | 95 | 9.7629 | 4.0657 | 0.4444 | 3.4207 | 3.4287 |
| 13.5895 | 0.4065 | 100 | 9.5797 | 4.1563 | 0.4675 | 3.4797 | 3.4807 |
| 13.5211 | 0.4268 | 105 | 9.3524 | 4.1978 | 0.4748 | 3.5357 | 3.5418 |
| 14.1282 | 0.4472 | 110 | 9.1117 | 4.2016 | 0.4745 | 3.5392 | 3.5417 |
| 13.0696 | 0.4675 | 115 | 8.9185 | 4.1619 | 0.4581 | 3.5058 | 3.5053 |
| 13.5505 | 0.4878 | 120 | 8.7076 | 4.0617 | 0.4730 | 3.4863 | 3.4884 |
| 12.7191 | 0.5081 | 125 | 8.5103 | 4.1287 | 0.5343 | 3.5354 | 3.5418 |
| 11.9604 | 0.5285 | 130 | 8.3253 | 4.2676 | 0.5616 | 3.6476 | 3.6568 |
| 12.1359 | 0.5488 | 135 | 8.1128 | 4.2319 | 0.5450 | 3.6035 | 3.6020 |
| 12.6743 | 0.5691 | 140 | 7.9260 | 4.1931 | 0.4958 | 3.5669 | 3.5720 |
| 10.8556 | 0.5894 | 145 | 7.7804 | 4.3623 | 0.5388 | 3.6812 | 3.6801 |
| 10.6165 | 0.6098 | 150 | 7.6086 | 4.2635 | 0.4790 | 3.6205 | 3.6191 |
| 10.3137 | 0.6301 | 155 | 7.4471 | 4.3057 | 0.5036 | 3.6870 | 3.6775 |
| 10.8264 | 0.6504 | 160 | 7.3016 | 4.2296 | 0.4382 | 3.6120 | 3.6114 |
| 9.707 | 0.6707 | 165 | 7.1770 | 4.4023 | 0.4457 | 3.7598 | 3.7648 |
| 9.0948 | 0.6911 | 170 | 7.0761 | 4.2964 | 0.4772 | 3.7047 | 3.7047 |
| 8.9284 | 0.7114 | 175 | 6.9906 | 4.2649 | 0.4765 | 3.7074 | 3.7053 |
| 8.8882 | 0.7317 | 180 | 6.9178 | 4.0879 | 0.4358 | 3.5706 | 3.5620 |
| 8.4453 | 0.7520 | 185 | 6.8269 | 3.9639 | 0.4308 | 3.4378 | 3.4379 |
| 9.0233 | 0.7724 | 190 | 6.7421 | 3.9524 | 0.4346 | 3.4217 | 3.4278 |
| 8.6501 | 0.7927 | 195 | 6.6840 | 3.8078 | 0.4012 | 3.3565 | 3.3576 |
| 7.8102 | 0.8130 | 200 | 6.6259 | 3.6878 | 0.3628 | 3.2840 | 3.2853 |
| 8.1242 | 0.8333 | 205 | 6.5638 | 3.6267 | 0.3355 | 3.2284 | 3.2301 |
| 8.1765 | 0.8537 | 210 | 6.5169 | 3.5751 | 0.3065 | 3.1854 | 3.1917 |
| 7.8745 | 0.8740 | 215 | 6.4719 | 3.3769 | 0.2566 | 3.0335 | 3.0340 |
| 7.9458 | 0.8943 | 220 | 6.4389 | 3.3340 | 0.2057 | 3.0079 | 3.0027 |
| 7.7474 | 0.9146 | 225 | 6.4035 | 3.3362 | 0.1940 | 3.0041 | 3.0107 |
| 7.7163 | 0.9350 | 230 | 6.3660 | 3.2909 | 0.1677 | 3.0005 | 2.9987 |
| 7.8728 | 0.9553 | 235 | 6.3361 | 3.2088 | 0.1610 | 2.9360 | 2.9278 |
| 7.7745 | 0.9756 | 240 | 6.3165 | 3.1927 | 0.1512 | 2.9150 | 2.9103 |
| 7.2384 | 0.9959 | 245 | 6.2932 | 3.1423 | 0.1330 | 2.8801 | 2.8714 |
| 7.3485 | 1.0163 | 250 | 6.2603 | 3.1407 | 0.1053 | 2.8848 | 2.8752 |
| 7.3794 | 1.0366 | 255 | 6.2228 | 3.0919 | 0.1009 | 2.8536 | 2.8508 |
| 7.3728 | 1.0569 | 260 | 6.1948 | 3.1268 | 0.1007 | 2.8836 | 2.8856 |
| 7.0395 | 1.0772 | 265 | 6.1632 | 3.0872 | 0.1005 | 2.8595 | 2.8619 |
| 6.8601 | 1.0976 | 270 | 6.1160 | 3.1920 | 0.1046 | 2.9322 | 2.9324 |
| 6.9111 | 1.1179 | 275 | 6.0558 | 3.3381 | 0.1192 | 3.0477 | 3.0529 |
| 6.9279 | 1.1382 | 280 | 5.9855 | 3.4293 | 0.1258 | 3.1141 | 3.1218 |
| 6.7801 | 1.1585 | 285 | 5.9176 | 3.4325 | 0.1198 | 3.1306 | 3.1407 |
| 6.7719 | 1.1789 | 290 | 5.8450 | 3.4232 | 0.0948 | 3.1421 | 3.1511 |
| 6.4791 | 1.1992 | 295 | 5.7314 | 3.4339 | 0.0908 | 3.1751 | 3.1826 |
| 6.5032 | 1.2195 | 300 | 5.6052 | 3.5594 | 0.1161 | 3.2799 | 3.2848 |
| 6.3077 | 1.2398 | 305 | 5.4308 | 3.8246 | 0.1526 | 3.4515 | 3.4549 |
| 6.1347 | 1.2602 | 310 | 5.2257 | 4.1937 | 0.2871 | 3.6908 | 3.6980 |
| 6.3168 | 1.2805 | 315 | 5.0692 | 4.3388 | 0.3095 | 3.7995 | 3.8041 |
| 6.1956 | 1.3008 | 320 | 4.9395 | 4.5952 | 0.3955 | 3.9670 | 3.9778 |
| 6.1062 | 1.3211 | 325 | 4.8052 | 5.0407 | 0.5409 | 4.2583 | 4.2650 |
| 5.882 | 1.3415 | 330 | 4.6693 | 5.2838 | 0.5466 | 4.4464 | 4.4589 |
| 5.8539 | 1.3618 | 335 | 4.5528 | 5.5252 | 0.5439 | 4.5970 | 4.6022 |
| 5.4454 | 1.3821 | 340 | 4.4366 | 5.8765 | 0.5977 | 4.8259 | 4.8281 |
| 5.6131 | 1.4024 | 345 | 4.3597 | 6.1999 | 0.6578 | 5.0213 | 5.0229 |
| 5.3551 | 1.4228 | 350 | 4.3115 | 6.2530 | 0.6767 | 5.0826 | 5.0748 |
| 5.1463 | 1.4431 | 355 | 4.2637 | 6.2949 | 0.6428 | 5.0490 | 5.0560 |
| 5.1476 | 1.4634 | 360 | 4.2049 | 6.5195 | 0.7002 | 5.2668 | 5.2701 |
| 5.073 | 1.4837 | 365 | 4.1581 | 6.7561 | 0.8051 | 5.4618 | 5.4527 |
| 5.1701 | 1.5041 | 370 | 4.1223 | 6.7501 | 0.7622 | 5.5161 | 5.5117 |
| 5.1188 | 1.5244 | 375 | 4.0904 | 6.6304 | 0.7352 | 5.4031 | 5.3876 |
| 5.0913 | 1.5447 | 380 | 4.0580 | 6.5183 | 0.7388 | 5.3353 | 5.3260 |
| 5.1114 | 1.5650 | 385 | 4.0236 | 6.3151 | 0.7055 | 5.1585 | 5.1491 |
| 4.7303 | 1.5854 | 390 | 3.9958 | 6.3426 | 0.7244 | 5.1699 | 5.1643 |
| 4.9915 | 1.6057 | 395 | 3.9675 | 6.5585 | 0.7586 | 5.2496 | 5.2469 |
| 4.9144 | 1.6260 | 400 | 3.9462 | 6.5973 | 0.7327 | 5.2719 | 5.2706 |
| 4.7182 | 1.6463 | 405 | 3.9244 | 6.7598 | 0.8297 | 5.4072 | 5.3997 |
| 4.7528 | 1.6667 | 410 | 3.9015 | 6.6425 | 0.7974 | 5.4003 | 5.3979 |
| 4.6383 | 1.6870 | 415 | 3.8839 | 6.6935 | 0.7657 | 5.4553 | 5.4618 |
| 4.6681 | 1.7073 | 420 | 3.8663 | 6.6632 | 0.7815 | 5.4305 | 5.4345 |
| 4.5091 | 1.7276 | 425 | 3.8536 | 6.6817 | 0.8054 | 5.4240 | 5.4254 |
| 4.7573 | 1.7480 | 430 | 3.8444 | 6.7848 | 0.8458 | 5.3968 | 5.4036 |
| 4.5883 | 1.7683 | 435 | 3.8353 | 6.8255 | 0.8781 | 5.4295 | 5.4383 |
| 4.813 | 1.7886 | 440 | 3.8243 | 6.9426 | 0.8849 | 5.5732 | 5.5796 |
| 4.8158 | 1.8089 | 445 | 3.8155 | 6.9445 | 0.8937 | 5.6175 | 5.6261 |
| 4.8598 | 1.8293 | 450 | 3.8080 | 6.9469 | 0.9113 | 5.6107 | 5.6260 |
| 4.4413 | 1.8496 | 455 | 3.7979 | 7.0513 | 0.9088 | 5.6948 | 5.7109 |
| 4.5718 | 1.8699 | 460 | 3.7883 | 7.0571 | 0.8827 | 5.6223 | 5.6259 |
| 4.5612 | 1.8902 | 465 | 3.7809 | 7.2025 | 0.9906 | 5.7196 | 5.7318 |
| 4.4533 | 1.9106 | 470 | 3.7743 | 7.3264 | 1.0365 | 5.8895 | 5.8971 |
| 4.6964 | 1.9309 | 475 | 3.7670 | 7.2795 | 1.0343 | 5.8303 | 5.8344 |
| 4.4532 | 1.9512 | 480 | 3.7606 | 7.2770 | 1.0298 | 5.8453 | 5.8516 |
| 4.4845 | 1.9715 | 485 | 3.7572 | 7.1885 | 1.0745 | 5.8021 | 5.8125 |
| 4.5913 | 1.9919 | 490 | 3.7540 | 7.1857 | 1.0814 | 5.8054 | 5.8130 |
| 4.4704 | 2.0122 | 495 | 3.7503 | 7.2876 | 1.0921 | 5.9138 | 5.9150 |
| 4.4753 | 2.0325 | 500 | 3.7453 | 7.3807 | 1.1092 | 5.9596 | 5.9700 |
| 4.4391 | 2.0528 | 505 | 3.7409 | 7.4010 | 1.0870 | 5.9533 | 5.9628 |
| 4.4315 | 2.0732 | 510 | 3.7382 | 7.3382 | 1.1040 | 5.9099 | 5.9189 |
| 4.2783 | 2.0935 | 515 | 3.7349 | 7.2988 | 1.0887 | 5.8870 | 5.8919 |
| 4.3117 | 2.1138 | 520 | 3.7307 | 7.3069 | 1.0594 | 5.9009 | 5.9126 |
| 4.318 | 2.1341 | 525 | 3.7271 | 7.3261 | 1.0414 | 5.9149 | 5.9164 |
| 4.2801 | 2.1545 | 530 | 3.7242 | 7.3054 | 1.0500 | 5.8905 | 5.8894 |
| 4.6391 | 2.1748 | 535 | 3.7208 | 7.3645 | 1.0492 | 5.9397 | 5.9380 |
| 4.3956 | 2.1951 | 540 | 3.7156 | 7.4189 | 1.1015 | 5.9650 | 5.9696 |
| 4.421 | 2.2154 | 545 | 3.7123 | 7.3371 | 1.0676 | 5.8936 | 5.9028 |
| 4.4005 | 2.2358 | 550 | 3.7090 | 7.3309 | 1.0480 | 5.9009 | 5.8999 |
| 4.363 | 2.2561 | 555 | 3.7065 | 7.2813 | 1.0386 | 5.8488 | 5.8472 |
| 4.3898 | 2.2764 | 560 | 3.7041 | 7.2897 | 1.0231 | 5.8119 | 5.8203 |
| 4.4024 | 2.2967 | 565 | 3.7014 | 7.2729 | 0.9973 | 5.8061 | 5.8105 |
| 4.2522 | 2.3171 | 570 | 3.7001 | 7.3704 | 1.0285 | 5.8480 | 5.8460 |
| 4.2606 | 2.3374 | 575 | 3.6985 | 7.3538 | 1.0364 | 5.8260 | 5.8280 |
| 4.5745 | 2.3577 | 580 | 3.6977 | 7.3535 | 1.0351 | 5.8424 | 5.8435 |
| 4.5558 | 2.3780 | 585 | 3.6959 | 7.3292 | 1.0259 | 5.8504 | 5.8529 |
| 4.29 | 2.3984 | 590 | 3.6928 | 7.3560 | 1.0402 | 5.8870 | 5.8893 |
| 4.4577 | 2.4187 | 595 | 3.6897 | 7.3185 | 1.0389 | 5.8524 | 5.8577 |
| 4.3417 | 2.4390 | 600 | 3.6872 | 7.2916 | 1.0302 | 5.8332 | 5.8447 |
| 4.3844 | 2.4593 | 605 | 3.6861 | 7.2599 | 1.0272 | 5.8240 | 5.8345 |
| 4.2335 | 2.4797 | 610 | 3.6858 | 7.3136 | 1.0066 | 5.8726 | 5.8854 |
| 4.2669 | 2.5 | 615 | 3.6854 | 7.3474 | 1.0671 | 5.9062 | 5.9133 |
| 4.3353 | 2.5203 | 620 | 3.6842 | 7.3982 | 1.0725 | 5.9494 | 5.9494 |
| 4.1778 | 2.5407 | 625 | 3.6834 | 7.4003 | 1.0443 | 5.9376 | 5.9381 |
| 4.1977 | 2.5610 | 630 | 3.6823 | 7.4257 | 1.0581 | 5.9566 | 5.9641 |
| 4.1946 | 2.5813 | 635 | 3.6810 | 7.4195 | 1.0472 | 5.9493 | 5.9564 |
| 4.2247 | 2.6016 | 640 | 3.6798 | 7.4042 | 1.0559 | 5.9337 | 5.9440 |
| 4.0221 | 2.6220 | 645 | 3.6784 | 7.3767 | 1.0109 | 5.8896 | 5.8969 |
| 4.0861 | 2.6423 | 650 | 3.6780 | 7.3535 | 1.0284 | 5.8929 | 5.8947 |
| 4.5216 | 2.6626 | 655 | 3.6776 | 7.4155 | 1.0361 | 5.9195 | 5.9223 |
| 4.5452 | 2.6829 | 660 | 3.6759 | 7.3827 | 1.0340 | 5.8694 | 5.8700 |
| 4.2545 | 2.7033 | 665 | 3.6737 | 7.2863 | 1.0115 | 5.8254 | 5.8315 |
| 4.2745 | 2.7236 | 670 | 3.6717 | 7.3155 | 1.0193 | 5.8232 | 5.8272 |
| 4.0946 | 2.7439 | 675 | 3.6704 | 7.3085 | 0.9942 | 5.8310 | 5.8384 |
| 4.1751 | 2.7642 | 680 | 3.6698 | 7.2713 | 0.9714 | 5.7913 | 5.7933 |
| 4.2766 | 2.7846 | 685 | 3.6698 | 7.3288 | 0.9622 | 5.7999 | 5.8011 |
| 4.2975 | 2.8049 | 690 | 3.6691 | 7.3673 | 0.9866 | 5.8446 | 5.8462 |
| 4.259 | 2.8252 | 695 | 3.6677 | 7.3719 | 0.9800 | 5.8379 | 5.8402 |
| 4.1375 | 2.8455 | 700 | 3.6658 | 7.3096 | 0.9819 | 5.7909 | 5.7937 |
| 4.1123 | 2.8659 | 705 | 3.6639 | 7.3239 | 0.9947 | 5.7972 | 5.8001 |
| 4.3939 | 2.8862 | 710 | 3.6620 | 7.3352 | 1.0033 | 5.7864 | 5.7918 |
| 4.3558 | 2.9065 | 715 | 3.6605 | 7.2803 | 0.9570 | 5.7227 | 5.7274 |
| 4.2339 | 2.9268 | 720 | 3.6593 | 7.2910 | 0.9812 | 5.7466 | 5.7553 |
| 4.3709 | 2.9472 | 725 | 3.6581 | 7.3238 | 0.9818 | 5.7739 | 5.7823 |
| 4.2776 | 2.9675 | 730 | 3.6574 | 7.3445 | 1.0330 | 5.8094 | 5.8181 |
| 4.1297 | 2.9878 | 735 | 3.6567 | 7.3059 | 1.0122 | 5.7926 | 5.8050 |
| 4.0283 | 3.0081 | 740 | 3.6563 | 7.3800 | 1.0397 | 5.8484 | 5.8597 |
| 4.1927 | 3.0285 | 745 | 3.6557 | 7.4114 | 1.0440 | 5.8713 | 5.8851 |
| 4.211 | 3.0488 | 750 | 3.6550 | 7.4497 | 1.0687 | 5.8968 | 5.9149 |
| 4.2516 | 3.0691 | 755 | 3.6543 | 7.3851 | 1.0738 | 5.8845 | 5.8986 |
| 4.2483 | 3.0894 | 760 | 3.6537 | 7.3906 | 1.0650 | 5.8817 | 5.8902 |
| 4.1612 | 3.1098 | 765 | 3.6526 | 7.3874 | 1.0756 | 5.8775 | 5.8829 |
| 4.2832 | 3.1301 | 770 | 3.6523 | 7.3994 | 1.0785 | 5.8812 | 5.8828 |
| 4.1306 | 3.1504 | 775 | 3.6520 | 7.4652 | 1.0993 | 5.9060 | 5.9157 |
| 4.1866 | 3.1707 | 780 | 3.6514 | 7.4709 | 1.0999 | 5.9119 | 5.9281 |
| 4.2834 | 3.1911 | 785 | 3.6513 | 7.4435 | 1.1007 | 5.8919 | 5.9057 |
| 4.2565 | 3.2114 | 790 | 3.6509 | 7.4210 | 1.1029 | 5.8853 | 5.8970 |
| 4.1566 | 3.2317 | 795 | 3.6506 | 7.4071 | 1.0829 | 5.8674 | 5.8756 |
| 4.1584 | 3.2520 | 800 | 3.6506 | 7.4042 | 1.0822 | 5.8690 | 5.8797 |
| 4.2728 | 3.2724 | 805 | 3.6502 | 7.4338 | 1.0872 | 5.9021 | 5.9114 |
| 4.2469 | 3.2927 | 810 | 3.6495 | 7.4174 | 1.0871 | 5.8931 | 5.8974 |
| 4.1297 | 3.3130 | 815 | 3.6486 | 7.4335 | 1.0861 | 5.9093 | 5.9129 |
| 4.1833 | 3.3333 | 820 | 3.6479 | 7.3910 | 1.0857 | 5.8893 | 5.8916 |
| 4.1635 | 3.3537 | 825 | 3.6476 | 7.3714 | 1.0801 | 5.8781 | 5.8791 |
| 3.9877 | 3.3740 | 830 | 3.6473 | 7.4043 | 1.0756 | 5.8988 | 5.9025 |
| 4.1508 | 3.3943 | 835 | 3.6471 | 7.3886 | 1.1179 | 5.9008 | 5.9095 |
| 4.3126 | 3.4146 | 840 | 3.6462 | 7.4321 | 1.1149 | 5.9282 | 5.9401 |
| 4.0401 | 3.4350 | 845 | 3.6451 | 7.4416 | 1.1107 | 5.9291 | 5.9376 |
| 4.3478 | 3.4553 | 850 | 3.6443 | 7.4642 | 1.1471 | 5.9633 | 5.9683 |
| 4.2058 | 3.4756 | 855 | 3.6434 | 7.4925 | 1.1631 | 5.9774 | 5.9888 |
| 4.1838 | 3.4959 | 860 | 3.6429 | 7.4792 | 1.1740 | 5.9757 | 5.9832 |
| 4.2264 | 3.5163 | 865 | 3.6425 | 7.4400 | 1.1621 | 5.9491 | 5.9554 |
| 4.4029 | 3.5366 | 870 | 3.6423 | 7.4487 | 1.1656 | 5.9588 | 5.9652 |
| 4.2859 | 3.5569 | 875 | 3.6424 | 7.3773 | 1.1202 | 5.8960 | 5.8970 |
| 3.9724 | 3.5772 | 880 | 3.6421 | 7.4120 | 1.1085 | 5.8966 | 5.9021 |
| 4.1194 | 3.5976 | 885 | 3.6419 | 7.4185 | 1.1191 | 5.8907 | 5.8964 |
| 4.2119 | 3.6179 | 890 | 3.6418 | 7.4229 | 1.1225 | 5.8875 | 5.8906 |
| 4.31 | 3.6382 | 895 | 3.6417 | 7.4117 | 1.1135 | 5.8895 | 5.8924 |
| 4.1687 | 3.6585 | 900 | 3.6414 | 7.4160 | 1.1085 | 5.8995 | 5.9034 |
| 4.2521 | 3.6789 | 905 | 3.6410 | 7.4245 | 1.1163 | 5.9010 | 5.9052 |
| 4.2049 | 3.6992 | 910 | 3.6410 | 7.4805 | 1.1203 | 5.9386 | 5.9397 |
| 4.1337 | 3.7195 | 915 | 3.6410 | 7.4671 | 1.1161 | 5.9266 | 5.9346 |
| 4.2343 | 3.7398 | 920 | 3.6408 | 7.4772 | 1.1250 | 5.9271 | 5.9351 |
| 4.2839 | 3.7602 | 925 | 3.6408 | 7.4479 | 1.1431 | 5.9088 | 5.9203 |
| 4.0611 | 3.7805 | 930 | 3.6405 | 7.4513 | 1.1501 | 5.9157 | 5.9203 |
| 4.1894 | 3.8008 | 935 | 3.6402 | 7.4433 | 1.1523 | 5.9014 | 5.9078 |
| 4.3014 | 3.8211 | 940 | 3.6400 | 7.4433 | 1.1523 | 5.9014 | 5.9078 |
| 4.2223 | 3.8415 | 945 | 3.6397 | 7.4435 | 1.1523 | 5.9094 | 5.9158 |
| 4.344 | 3.8618 | 950 | 3.6396 | 7.4501 | 1.1584 | 5.9262 | 5.9271 |
| 4.1072 | 3.8821 | 955 | 3.6395 | 7.4460 | 1.1544 | 5.9222 | 5.9231 |
| 4.1193 | 3.9024 | 960 | 3.6394 | 7.4422 | 1.1544 | 5.9222 | 5.9231 |
| 4.0124 | 3.9228 | 965 | 3.6393 | 7.4291 | 1.1467 | 5.9093 | 5.9130 |
| 4.1924 | 3.9431 | 970 | 3.6393 | 7.4291 | 1.1467 | 5.9093 | 5.9130 |
| 4.2722 | 3.9634 | 975 | 3.6392 | 7.4493 | 1.1542 | 5.9231 | 5.9247 |
| 4.1369 | 3.9837 | 980 | 3.6392 | 7.4493 | 1.1542 | 5.9231 | 5.9247 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0 |