Gemma-Medical-QA-LoRA
This model is a fine-tuned version of google/gemma-2b on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8668
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
3.2642 | 0.0103 | 100 | 2.9924 |
2.6906 | 0.0205 | 200 | 2.5289 |
2.4587 | 0.0308 | 300 | 2.3835 |
2.357 | 0.0411 | 400 | 2.3593 |
2.3804 | 0.0514 | 500 | 2.3834 |
2.3997 | 0.0616 | 600 | 2.4149 |
2.4127 | 0.0719 | 700 | 2.4326 |
2.4324 | 0.0822 | 800 | 2.4406 |
2.4394 | 0.0924 | 900 | 2.4357 |
2.4363 | 0.1027 | 1000 | 2.4273 |
2.4104 | 0.1130 | 1100 | 2.4209 |
2.4255 | 0.1232 | 1200 | 2.4175 |
2.4019 | 0.1335 | 1300 | 2.4075 |
2.4133 | 0.1438 | 1400 | 2.4035 |
2.3963 | 0.1541 | 1500 | 2.3965 |
2.3874 | 0.1643 | 1600 | 2.3951 |
2.382 | 0.1746 | 1700 | 2.3907 |
2.3827 | 0.1849 | 1800 | 2.3838 |
2.384 | 0.1951 | 1900 | 2.3715 |
2.3625 | 0.2054 | 2000 | 2.3617 |
2.353 | 0.2157 | 2100 | 2.3717 |
2.3554 | 0.2259 | 2200 | 2.3543 |
2.3426 | 0.2362 | 2300 | 2.3422 |
2.3522 | 0.2465 | 2400 | 2.3428 |
2.3355 | 0.2568 | 2500 | 2.3437 |
2.3451 | 0.2670 | 2600 | 2.3227 |
2.335 | 0.2773 | 2700 | 2.3303 |
2.3107 | 0.2876 | 2800 | 2.3312 |
2.3336 | 0.2978 | 2900 | 2.3223 |
2.3075 | 0.3081 | 3000 | 2.3116 |
2.2991 | 0.3184 | 3100 | 2.3155 |
2.3183 | 0.3286 | 3200 | 2.3094 |
2.3085 | 0.3389 | 3300 | 2.3035 |
2.3049 | 0.3492 | 3400 | 2.2998 |
2.3003 | 0.3595 | 3500 | 2.2944 |
2.3067 | 0.3697 | 3600 | 2.3003 |
2.2962 | 0.3800 | 3700 | 2.3012 |
2.2918 | 0.3903 | 3800 | 2.2859 |
2.2761 | 0.4005 | 3900 | 2.2826 |
2.2916 | 0.4108 | 4000 | 2.2703 |
2.2744 | 0.4211 | 4100 | 2.2754 |
2.2687 | 0.4313 | 4200 | 2.2646 |
2.2673 | 0.4416 | 4300 | 2.2654 |
2.2472 | 0.4519 | 4400 | 2.2617 |
2.2669 | 0.4622 | 4500 | 2.2536 |
2.2516 | 0.4724 | 4600 | 2.2585 |
2.2392 | 0.4827 | 4700 | 2.2514 |
2.2551 | 0.4930 | 4800 | 2.2445 |
2.2539 | 0.5032 | 4900 | 2.2380 |
2.2462 | 0.5135 | 5000 | 2.2374 |
2.2168 | 0.5238 | 5100 | 2.2376 |
2.2447 | 0.5340 | 5200 | 2.2272 |
2.2022 | 0.5443 | 5300 | 2.2081 |
2.2052 | 0.5546 | 5400 | 2.2144 |
2.213 | 0.5649 | 5500 | 2.2079 |
2.2078 | 0.5751 | 5600 | 2.2071 |
2.199 | 0.5854 | 5700 | 2.2007 |
2.2037 | 0.5957 | 5800 | 2.1961 |
2.2061 | 0.6059 | 5900 | 2.1962 |
2.1766 | 0.6162 | 6000 | 2.1861 |
2.1852 | 0.6265 | 6100 | 2.1868 |
2.1859 | 0.6367 | 6200 | 2.1777 |
2.1891 | 0.6470 | 6300 | 2.1753 |
2.1611 | 0.6573 | 6400 | 2.1712 |
2.1444 | 0.6676 | 6500 | 2.1659 |
2.157 | 0.6778 | 6600 | 2.1505 |
2.1554 | 0.6881 | 6700 | 2.1399 |
2.1344 | 0.6984 | 6800 | 2.1402 |
2.1306 | 0.7086 | 6900 | 2.1252 |
2.0952 | 0.7189 | 7000 | 2.1077 |
2.0969 | 0.7292 | 7100 | 2.0913 |
2.1258 | 0.7394 | 7200 | 2.0886 |
2.0826 | 0.7497 | 7300 | 2.0780 |
2.0782 | 0.7600 | 7400 | 2.0791 |
2.0802 | 0.7703 | 7500 | 2.0685 |
2.0786 | 0.7805 | 7600 | 2.0647 |
2.0618 | 0.7908 | 7700 | 2.0588 |
2.0593 | 0.8011 | 7800 | 2.0619 |
2.0643 | 0.8113 | 7900 | 2.0614 |
2.057 | 0.8216 | 8000 | 2.0661 |
2.0588 | 0.8319 | 8100 | 2.0524 |
2.0686 | 0.8421 | 8200 | 2.0546 |
2.0333 | 0.8524 | 8300 | 2.0496 |
2.0621 | 0.8627 | 8400 | 2.0474 |
2.023 | 0.8730 | 8500 | 2.0390 |
2.0507 | 0.8832 | 8600 | 2.0414 |
2.0476 | 0.8935 | 8700 | 2.0421 |
2.033 | 0.9038 | 8800 | 2.0400 |
2.0617 | 0.9140 | 8900 | 2.0383 |
2.0287 | 0.9243 | 9000 | 2.0441 |
2.0156 | 0.9346 | 9100 | 2.0335 |
2.0207 | 0.9448 | 9200 | 2.0337 |
2.036 | 0.9551 | 9300 | 2.0236 |
2.0411 | 0.9654 | 9400 | 2.0360 |
2.0277 | 0.9757 | 9500 | 2.0262 |
2.0449 | 0.9859 | 9600 | 2.0298 |
2.0323 | 0.9962 | 9700 | 2.0287 |
2.0124 | 1.0065 | 9800 | 2.0220 |
2.0211 | 1.0167 | 9900 | 2.0266 |
2.0137 | 1.0270 | 10000 | 2.0147 |
2.0169 | 1.0373 | 10100 | 2.0132 |
2.0075 | 1.0476 | 10200 | 2.0189 |
2.0022 | 1.0578 | 10300 | 2.0218 |
2.0172 | 1.0681 | 10400 | 2.0088 |
2.0152 | 1.0784 | 10500 | 2.0121 |
1.9993 | 1.0886 | 10600 | 2.0136 |
2.0109 | 1.0989 | 10700 | 2.0035 |
2.0155 | 1.1092 | 10800 | 2.0092 |
2.0101 | 1.1194 | 10900 | 2.0123 |
2.0028 | 1.1297 | 11000 | 2.0066 |
2.005 | 1.1400 | 11100 | 2.0060 |
2.0002 | 1.1503 | 11200 | 2.0026 |
1.994 | 1.1605 | 11300 | 2.0017 |
1.9938 | 1.1708 | 11400 | 2.0023 |
1.9896 | 1.1811 | 11500 | 2.0062 |
1.9957 | 1.1913 | 11600 | 1.9995 |
1.987 | 1.2016 | 11700 | 1.9973 |
2.0086 | 1.2119 | 11800 | 1.9899 |
1.994 | 1.2221 | 11900 | 1.9962 |
1.9668 | 1.2324 | 12000 | 1.9951 |
2.0094 | 1.2427 | 12100 | 1.9944 |
1.9898 | 1.2530 | 12200 | 1.9907 |
1.9958 | 1.2632 | 12300 | 1.9728 |
2.0 | 1.2735 | 12400 | 1.9864 |
1.9818 | 1.2838 | 12500 | 1.9907 |
2.0054 | 1.2940 | 12600 | 1.9877 |
1.9837 | 1.3043 | 12700 | 1.9925 |
1.9938 | 1.3146 | 12800 | 1.9869 |
2.0015 | 1.3248 | 12900 | 1.9958 |
1.9753 | 1.3351 | 13000 | 1.9873 |
1.9632 | 1.3454 | 13100 | 1.9920 |
1.9932 | 1.3557 | 13200 | 1.9782 |
1.9875 | 1.3659 | 13300 | 1.9777 |
1.9693 | 1.3762 | 13400 | 1.9826 |
1.9898 | 1.3865 | 13500 | 1.9748 |
1.9678 | 1.3967 | 13600 | 1.9892 |
1.989 | 1.4070 | 13700 | 1.9770 |
1.9789 | 1.4173 | 13800 | 1.9684 |
1.9733 | 1.4275 | 13900 | 1.9726 |
1.9623 | 1.4378 | 14000 | 1.9726 |
1.95 | 1.4481 | 14100 | 1.9733 |
1.9679 | 1.4584 | 14200 | 1.9689 |
1.964 | 1.4686 | 14300 | 1.9788 |
2.0041 | 1.4789 | 14400 | 1.9707 |
1.9626 | 1.4892 | 14500 | 1.9641 |
1.979 | 1.4994 | 14600 | 1.9682 |
1.9558 | 1.5097 | 14700 | 1.9677 |
1.9701 | 1.5200 | 14800 | 1.9677 |
1.976 | 1.5302 | 14900 | 1.9659 |
1.9448 | 1.5405 | 15000 | 1.9627 |
1.9494 | 1.5508 | 15100 | 1.9698 |
1.9552 | 1.5611 | 15200 | 1.9746 |
1.9628 | 1.5713 | 15300 | 1.9635 |
1.9589 | 1.5816 | 15400 | 1.9668 |
1.9769 | 1.5919 | 15500 | 1.9625 |
1.9513 | 1.6021 | 15600 | 1.9599 |
1.9578 | 1.6124 | 15700 | 1.9638 |
1.9694 | 1.6227 | 15800 | 1.9612 |
1.9508 | 1.6329 | 15900 | 1.9642 |
1.9568 | 1.6432 | 16000 | 1.9583 |
1.9474 | 1.6535 | 16100 | 1.9610 |
1.9616 | 1.6638 | 16200 | 1.9591 |
1.963 | 1.6740 | 16300 | 1.9621 |
1.9612 | 1.6843 | 16400 | 1.9602 |
1.959 | 1.6946 | 16500 | 1.9417 |
1.945 | 1.7048 | 16600 | 1.9535 |
1.9519 | 1.7151 | 16700 | 1.9553 |
1.9361 | 1.7254 | 16800 | 1.9538 |
1.9411 | 1.7356 | 16900 | 1.9450 |
1.9614 | 1.7459 | 17000 | 1.9579 |
1.9634 | 1.7562 | 17100 | 1.9546 |
1.9559 | 1.7665 | 17200 | 1.9501 |
1.9483 | 1.7767 | 17300 | 1.9491 |
1.9603 | 1.7870 | 17400 | 1.9529 |
1.9559 | 1.7973 | 17500 | 1.9495 |
1.9464 | 1.8075 | 17600 | 1.9491 |
1.9598 | 1.8178 | 17700 | 1.9499 |
1.9349 | 1.8281 | 17800 | 1.9512 |
1.9515 | 1.8383 | 17900 | 1.9454 |
1.9481 | 1.8486 | 18000 | 1.9423 |
1.9479 | 1.8589 | 18100 | 1.9486 |
1.944 | 1.8692 | 18200 | 1.9579 |
1.9333 | 1.8794 | 18300 | 1.9406 |
1.9489 | 1.8897 | 18400 | 1.9439 |
1.9603 | 1.9000 | 18500 | 1.9437 |
1.9349 | 1.9102 | 18600 | 1.9366 |
1.9453 | 1.9205 | 18700 | 1.9440 |
1.9199 | 1.9308 | 18800 | 1.9397 |
1.9554 | 1.9410 | 18900 | 1.9443 |
1.9256 | 1.9513 | 19000 | 1.9345 |
1.9393 | 1.9616 | 19100 | 1.9372 |
1.9432 | 1.9719 | 19200 | 1.9392 |
1.935 | 1.9821 | 19300 | 1.9379 |
1.9252 | 1.9924 | 19400 | 1.9459 |
1.9378 | 2.0027 | 19500 | 1.9403 |
1.9326 | 2.0129 | 19600 | 1.9400 |
1.9272 | 2.0232 | 19700 | 1.9380 |
1.9368 | 2.0335 | 19800 | 1.9408 |
1.9318 | 2.0438 | 19900 | 1.9284 |
1.9165 | 2.0540 | 20000 | 1.9395 |
1.941 | 2.0643 | 20100 | 1.9335 |
1.9236 | 2.0746 | 20200 | 1.9384 |
1.9222 | 2.0848 | 20300 | 1.9318 |
1.9242 | 2.0951 | 20400 | 1.9293 |
1.9262 | 2.1054 | 20500 | 1.9298 |
1.9149 | 2.1156 | 20600 | 1.9291 |
1.9226 | 2.1259 | 20700 | 1.9338 |
1.9393 | 2.1362 | 20800 | 1.9306 |
1.9294 | 2.1465 | 20900 | 1.9358 |
1.9275 | 2.1567 | 21000 | 1.9345 |
1.918 | 2.1670 | 21100 | 1.9332 |
1.9164 | 2.1773 | 21200 | 1.9240 |
1.9248 | 2.1875 | 21300 | 1.9302 |
1.9128 | 2.1978 | 21400 | 1.9341 |
1.9159 | 2.2081 | 21500 | 1.9217 |
1.934 | 2.2183 | 21600 | 1.9261 |
1.9258 | 2.2286 | 21700 | 1.9244 |
1.9034 | 2.2389 | 21800 | 1.9384 |
1.9023 | 2.2492 | 21900 | 1.9233 |
1.94 | 2.2594 | 22000 | 1.9232 |
1.9319 | 2.2697 | 22100 | 1.9289 |
1.8986 | 2.2800 | 22200 | 1.9191 |
1.9087 | 2.2902 | 22300 | 1.9196 |
1.9125 | 2.3005 | 22400 | 1.9235 |
1.9081 | 2.3108 | 22500 | 1.9103 |
1.9324 | 2.3210 | 22600 | 1.9249 |
1.9132 | 2.3313 | 22700 | 1.9210 |
1.9134 | 2.3416 | 22800 | 1.9273 |
1.923 | 2.3519 | 22900 | 1.9184 |
1.9271 | 2.3621 | 23000 | 1.9240 |
1.9089 | 2.3724 | 23100 | 1.9195 |
1.9232 | 2.3827 | 23200 | 1.9158 |
1.9153 | 2.3929 | 23300 | 1.9159 |
1.9303 | 2.4032 | 23400 | 1.9214 |
1.9267 | 2.4135 | 23500 | 1.9195 |
1.9041 | 2.4237 | 23600 | 1.9159 |
1.9104 | 2.4340 | 23700 | 1.9119 |
1.9126 | 2.4443 | 23800 | 1.9147 |
1.9179 | 2.4546 | 23900 | 1.9173 |
1.8934 | 2.4648 | 24000 | 1.9156 |
1.9213 | 2.4751 | 24100 | 1.9168 |
1.9244 | 2.4854 | 24200 | 1.9193 |
1.9064 | 2.4956 | 24300 | 1.9014 |
1.8898 | 2.5059 | 24400 | 1.9215 |
1.9063 | 2.5162 | 24500 | 1.9200 |
1.9105 | 2.5264 | 24600 | 1.9210 |
1.916 | 2.5367 | 24700 | 1.9113 |
1.9099 | 2.5470 | 24800 | 1.9090 |
1.9051 | 2.5573 | 24900 | 1.9060 |
1.9177 | 2.5675 | 25000 | 1.9181 |
1.923 | 2.5778 | 25100 | 1.9144 |
1.8971 | 2.5881 | 25200 | 1.9079 |
1.9133 | 2.5983 | 25300 | 1.9068 |
1.9318 | 2.6086 | 25400 | 1.9089 |
1.9149 | 2.6189 | 25500 | 1.9109 |
1.9145 | 2.6291 | 25600 | 1.9076 |
1.911 | 2.6394 | 25700 | 1.9149 |
1.8884 | 2.6497 | 25800 | 1.9018 |
1.8946 | 2.6600 | 25900 | 1.9217 |
1.9106 | 2.6702 | 26000 | 1.9082 |
1.906 | 2.6805 | 26100 | 1.9063 |
1.9026 | 2.6908 | 26200 | 1.9070 |
1.9088 | 2.7010 | 26300 | 1.9059 |
1.8938 | 2.7113 | 26400 | 1.9019 |
1.8964 | 2.7216 | 26500 | 1.9131 |
1.8947 | 2.7318 | 26600 | 1.9096 |
1.8906 | 2.7421 | 26700 | 1.9053 |
1.911 | 2.7524 | 26800 | 1.8969 |
1.887 | 2.7627 | 26900 | 1.9111 |
1.8864 | 2.7729 | 27000 | 1.9064 |
1.9195 | 2.7832 | 27100 | 1.9044 |
1.9129 | 2.7935 | 27200 | 1.9019 |
1.8915 | 2.8037 | 27300 | 1.8970 |
1.9035 | 2.8140 | 27400 | 1.9049 |
1.8755 | 2.8243 | 27500 | 1.8986 |
1.8939 | 2.8345 | 27600 | 1.8993 |
1.895 | 2.8448 | 27700 | 1.8978 |
1.8744 | 2.8551 | 27800 | 1.9052 |
1.9178 | 2.8654 | 27900 | 1.9040 |
1.8916 | 2.8756 | 28000 | 1.8977 |
1.9226 | 2.8859 | 28100 | 1.9014 |
1.8772 | 2.8962 | 28200 | 1.8990 |
1.9011 | 2.9064 | 28300 | 1.8888 |
1.8891 | 2.9167 | 28400 | 1.8998 |
1.91 | 2.9270 | 28500 | 1.8976 |
1.9288 | 2.9372 | 28600 | 1.8976 |
1.8759 | 2.9475 | 28700 | 1.9000 |
1.8806 | 2.9578 | 28800 | 1.9029 |
1.8971 | 2.9681 | 28900 | 1.8981 |
1.9036 | 2.9783 | 29000 | 1.8944 |
1.8898 | 2.9886 | 29100 | 1.8983 |
1.8935 | 2.9989 | 29200 | 1.8930 |
1.8838 | 3.0091 | 29300 | 1.9015 |
1.8964 | 3.0194 | 29400 | 1.9020 |
1.895 | 3.0297 | 29500 | 1.8909 |
1.8864 | 3.0400 | 29600 | 1.8871 |
1.89 | 3.0502 | 29700 | 1.8857 |
1.8846 | 3.0605 | 29800 | 1.8958 |
1.8983 | 3.0708 | 29900 | 1.8910 |
1.8917 | 3.0810 | 30000 | 1.8936 |
1.8913 | 3.0913 | 30100 | 1.8986 |
1.8559 | 3.1016 | 30200 | 1.9011 |
1.9041 | 3.1118 | 30300 | 1.8858 |
1.8752 | 3.1221 | 30400 | 1.8983 |
1.8813 | 3.1324 | 30500 | 1.8963 |
1.877 | 3.1427 | 30600 | 1.8924 |
1.8724 | 3.1529 | 30700 | 1.8895 |
1.8946 | 3.1632 | 30800 | 1.8942 |
1.8872 | 3.1735 | 30900 | 1.8940 |
1.8847 | 3.1837 | 31000 | 1.8931 |
1.8729 | 3.1940 | 31100 | 1.8850 |
1.8724 | 3.2043 | 31200 | 1.8911 |
1.864 | 3.2145 | 31300 | 1.8923 |
1.8824 | 3.2248 | 31400 | 1.8925 |
1.9007 | 3.2351 | 31500 | 1.8945 |
1.8993 | 3.2454 | 31600 | 1.8867 |
1.8687 | 3.2556 | 31700 | 1.8937 |
1.8768 | 3.2659 | 31800 | 1.8842 |
1.8744 | 3.2762 | 31900 | 1.8933 |
1.8877 | 3.2864 | 32000 | 1.8901 |
1.8644 | 3.2967 | 32100 | 1.8798 |
1.8631 | 3.3070 | 32200 | 1.8890 |
1.8833 | 3.3172 | 32300 | 1.8862 |
1.8889 | 3.3275 | 32400 | 1.8835 |
1.8934 | 3.3378 | 32500 | 1.8858 |
1.8905 | 3.3481 | 32600 | 1.8856 |
1.8965 | 3.3583 | 32700 | 1.8882 |
1.8833 | 3.3686 | 32800 | 1.8845 |
1.9017 | 3.3789 | 32900 | 1.8835 |
1.8885 | 3.3891 | 33000 | 1.8821 |
1.8852 | 3.3994 | 33100 | 1.8903 |
1.8727 | 3.4097 | 33200 | 1.8796 |
1.8788 | 3.4199 | 33300 | 1.8892 |
1.8609 | 3.4302 | 33400 | 1.8792 |
1.9 | 3.4405 | 33500 | 1.8748 |
1.8731 | 3.4508 | 33600 | 1.8825 |
1.8753 | 3.4610 | 33700 | 1.8773 |
1.8651 | 3.4713 | 33800 | 1.8853 |
1.8757 | 3.4816 | 33900 | 1.8819 |
1.8939 | 3.4918 | 34000 | 1.8832 |
1.8939 | 3.5021 | 34100 | 1.8811 |
1.8719 | 3.5124 | 34200 | 1.8812 |
1.859 | 3.5226 | 34300 | 1.8834 |
1.8866 | 3.5329 | 34400 | 1.8762 |
1.888 | 3.5432 | 34500 | 1.8834 |
1.8816 | 3.5535 | 34600 | 1.8836 |
1.8855 | 3.5637 | 34700 | 1.8837 |
1.8731 | 3.5740 | 34800 | 1.8829 |
1.9 | 3.5843 | 34900 | 1.8847 |
1.8767 | 3.5945 | 35000 | 1.8773 |
1.8847 | 3.6048 | 35100 | 1.8841 |
1.8716 | 3.6151 | 35200 | 1.8773 |
1.8746 | 3.6253 | 35300 | 1.8905 |
1.8672 | 3.6356 | 35400 | 1.8835 |
1.8825 | 3.6459 | 35500 | 1.8796 |
1.8711 | 3.6562 | 35600 | 1.8781 |
1.873 | 3.6664 | 35700 | 1.8787 |
1.8841 | 3.6767 | 35800 | 1.8774 |
1.8668 | 3.6870 | 35900 | 1.8827 |
1.8642 | 3.6972 | 36000 | 1.8804 |
1.8813 | 3.7075 | 36100 | 1.8761 |
1.8602 | 3.7178 | 36200 | 1.8772 |
1.8772 | 3.7280 | 36300 | 1.8859 |
1.8847 | 3.7383 | 36400 | 1.8792 |
1.8737 | 3.7486 | 36500 | 1.8823 |
1.8683 | 3.7589 | 36600 | 1.8812 |
1.8731 | 3.7691 | 36700 | 1.8808 |
1.8467 | 3.7794 | 36800 | 1.8828 |
1.8877 | 3.7897 | 36900 | 1.8820 |
1.8751 | 3.7999 | 37000 | 1.8840 |
1.8967 | 3.8102 | 37100 | 1.8824 |
1.8898 | 3.8205 | 37200 | 1.8747 |
1.8772 | 3.8307 | 37300 | 1.8736 |
1.8989 | 3.8410 | 37400 | 1.8733 |
1.8636 | 3.8513 | 37500 | 1.8791 |
1.8806 | 3.8616 | 37600 | 1.8731 |
1.8825 | 3.8718 | 37700 | 1.8811 |
1.8693 | 3.8821 | 37800 | 1.8753 |
1.8534 | 3.8924 | 37900 | 1.8731 |
1.867 | 3.9026 | 38000 | 1.8765 |
1.876 | 3.9129 | 38100 | 1.8801 |
1.848 | 3.9232 | 38200 | 1.8709 |
1.8628 | 3.9334 | 38300 | 1.8739 |
1.8634 | 3.9437 | 38400 | 1.8734 |
1.8691 | 3.9540 | 38500 | 1.8747 |
1.8676 | 3.9643 | 38600 | 1.8748 |
1.874 | 3.9745 | 38700 | 1.8745 |
1.8757 | 3.9848 | 38800 | 1.8797 |
1.8573 | 3.9951 | 38900 | 1.8741 |
1.8578 | 4.0053 | 39000 | 1.8765 |
1.8755 | 4.0156 | 39100 | 1.8761 |
1.885 | 4.0259 | 39200 | 1.8760 |
1.8647 | 4.0362 | 39300 | 1.8759 |
1.8642 | 4.0464 | 39400 | 1.8760 |
1.8838 | 4.0567 | 39500 | 1.8747 |
1.8632 | 4.0670 | 39600 | 1.8747 |
1.881 | 4.0772 | 39700 | 1.8758 |
1.8661 | 4.0875 | 39800 | 1.8699 |
1.8748 | 4.0978 | 39900 | 1.8723 |
1.8593 | 4.1080 | 40000 | 1.8688 |
1.8781 | 4.1183 | 40100 | 1.8698 |
1.847 | 4.1286 | 40200 | 1.8751 |
1.8534 | 4.1389 | 40300 | 1.8682 |
1.856 | 4.1491 | 40400 | 1.8704 |
1.8735 | 4.1594 | 40500 | 1.8710 |
1.8586 | 4.1697 | 40600 | 1.8695 |
1.8466 | 4.1799 | 40700 | 1.8686 |
1.8594 | 4.1902 | 40800 | 1.8692 |
1.86 | 4.2005 | 40900 | 1.8674 |
1.8643 | 4.2107 | 41000 | 1.8693 |
1.8446 | 4.2210 | 41100 | 1.8685 |
1.8578 | 4.2313 | 41200 | 1.8710 |
1.8473 | 4.2416 | 41300 | 1.8716 |
1.865 | 4.2518 | 41400 | 1.8724 |
1.848 | 4.2621 | 41500 | 1.8731 |
1.864 | 4.2724 | 41600 | 1.8684 |
1.8584 | 4.2826 | 41700 | 1.8753 |
1.842 | 4.2929 | 41800 | 1.8666 |
1.8735 | 4.3032 | 41900 | 1.8692 |
1.8621 | 4.3134 | 42000 | 1.8674 |
1.8604 | 4.3237 | 42100 | 1.8626 |
1.8586 | 4.3340 | 42200 | 1.8696 |
1.8914 | 4.3443 | 42300 | 1.8684 |
1.8752 | 4.3545 | 42400 | 1.8671 |
1.8856 | 4.3648 | 42500 | 1.8719 |
1.8712 | 4.3751 | 42600 | 1.8729 |
1.8535 | 4.3853 | 42700 | 1.8719 |
1.8787 | 4.3956 | 42800 | 1.8674 |
1.8659 | 4.4059 | 42900 | 1.8709 |
1.8818 | 4.4161 | 43000 | 1.8713 |
1.8459 | 4.4264 | 43100 | 1.8723 |
1.8766 | 4.4367 | 43200 | 1.8668 |
1.8629 | 4.4470 | 43300 | 1.8678 |
1.8594 | 4.4572 | 43400 | 1.8687 |
1.8589 | 4.4675 | 43500 | 1.8716 |
1.8755 | 4.4778 | 43600 | 1.8665 |
1.8526 | 4.4880 | 43700 | 1.8656 |
1.8675 | 4.4983 | 43800 | 1.8727 |
1.8503 | 4.5086 | 43900 | 1.8705 |
1.8606 | 4.5188 | 44000 | 1.8736 |
1.8677 | 4.5291 | 44100 | 1.8683 |
1.8571 | 4.5394 | 44200 | 1.8712 |
1.8752 | 4.5497 | 44300 | 1.8710 |
1.8528 | 4.5599 | 44400 | 1.8697 |
1.8815 | 4.5702 | 44500 | 1.8689 |
1.8768 | 4.5805 | 44600 | 1.8672 |
1.8815 | 4.5907 | 44700 | 1.8740 |
1.8539 | 4.6010 | 44800 | 1.8704 |
1.8776 | 4.6113 | 44900 | 1.8652 |
1.8446 | 4.6215 | 45000 | 1.8678 |
1.8704 | 4.6318 | 45100 | 1.8683 |
1.8522 | 4.6421 | 45200 | 1.8668 |
1.8827 | 4.6524 | 45300 | 1.8673 |
1.851 | 4.6626 | 45400 | 1.8652 |
1.8577 | 4.6729 | 45500 | 1.8638 |
1.8581 | 4.6832 | 45600 | 1.8694 |
1.851 | 4.6934 | 45700 | 1.8675 |
1.8563 | 4.7037 | 45800 | 1.8704 |
1.8778 | 4.7140 | 45900 | 1.8656 |
1.8597 | 4.7242 | 46000 | 1.8676 |
1.8501 | 4.7345 | 46100 | 1.8684 |
1.8608 | 4.7448 | 46200 | 1.8684 |
1.8609 | 4.7551 | 46300 | 1.8687 |
1.8681 | 4.7653 | 46400 | 1.8649 |
1.8625 | 4.7756 | 46500 | 1.8672 |
1.8467 | 4.7859 | 46600 | 1.8681 |
1.8359 | 4.7961 | 46700 | 1.8669 |
1.855 | 4.8064 | 46800 | 1.8667 |
1.8551 | 4.8167 | 46900 | 1.8662 |
1.8658 | 4.8269 | 47000 | 1.8655 |
1.8621 | 4.8372 | 47100 | 1.8682 |
1.8679 | 4.8475 | 47200 | 1.8691 |
1.8653 | 4.8578 | 47300 | 1.8669 |
1.8427 | 4.8680 | 47400 | 1.8645 |
1.8538 | 4.8783 | 47500 | 1.8658 |
1.8617 | 4.8886 | 47600 | 1.8656 |
1.8693 | 4.8988 | 47700 | 1.8661 |
1.8379 | 4.9091 | 47800 | 1.8668 |
1.8709 | 4.9194 | 47900 | 1.8673 |
1.8537 | 4.9296 | 48000 | 1.8664 |
1.8568 | 4.9399 | 48100 | 1.8664 |
1.867 | 4.9502 | 48200 | 1.8661 |
1.8591 | 4.9605 | 48300 | 1.8658 |
1.8565 | 4.9707 | 48400 | 1.8661 |
1.8541 | 4.9810 | 48500 | 1.8667 |
1.8736 | 4.9913 | 48600 | 1.8668 |
Framework versions
- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 1.13.1+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1
- Downloads last month
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Model tree for aryaadhi/Gemma-Medical-QA-LoRA
Base model
google/gemma-2b