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---
base_model: Daewon0808/prm800k_qwen_fulltune
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: v4_qwen_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. -->
# v4_qwen_lora
This model is a fine-tuned version of [Daewon0808/prm800k_qwen_fulltune](https://huggingface.co/Daewon0808/prm800k_qwen_fulltune) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1986
- Prm accuracy: 0.9216
- Prm precision: 0.9710
- Prm recall: 0.9178
- Prm specificty: 0.9310
- Prm npv: 0.8182
- Prm f1: 0.9437
- Prm f1 neg: 0.8710
- Prm f1 auc: 0.9244
- Prm f1 auc (fixed): 0.9502
## 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: 2
- eval_batch_size: 4
- seed: 908932403
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Prm accuracy | Prm precision | Prm recall | Prm specificty | Prm npv | Prm f1 | Prm f1 neg | Prm f1 auc | Prm f1 auc (fixed) |
|:-------------:|:------:|:----:|:---------------:|:------------:|:-------------:|:----------:|:--------------:|:-------:|:------:|:----------:|:----------:|:------------------:|
| No log | 0 | 0 | 0.4028 | 0.8039 | 0.9344 | 0.7808 | 0.8621 | 0.6098 | 0.8507 | 0.7143 | 0.8214 | 0.8420 |
| 0.4957 | 0.0113 | 5 | 0.4020 | 0.8039 | 0.9344 | 0.7808 | 0.8621 | 0.6098 | 0.8507 | 0.7143 | 0.8214 | 0.8427 |
| 0.4552 | 0.0225 | 10 | 0.4001 | 0.8039 | 0.9344 | 0.7808 | 0.8621 | 0.6098 | 0.8507 | 0.7143 | 0.8214 | 0.8451 |
| 0.4974 | 0.0338 | 15 | 0.3895 | 0.8431 | 0.9385 | 0.8356 | 0.8621 | 0.6757 | 0.8841 | 0.7576 | 0.8488 | 0.8467 |
| 0.4715 | 0.0451 | 20 | 0.3655 | 0.8824 | 0.9420 | 0.8904 | 0.8621 | 0.7576 | 0.9155 | 0.8065 | 0.8762 | 0.8517 |
| 0.4215 | 0.0563 | 25 | 0.3386 | 0.9020 | 0.9437 | 0.9178 | 0.8621 | 0.8065 | 0.9306 | 0.8333 | 0.8899 | 0.8573 |
| 0.4069 | 0.0676 | 30 | 0.3204 | 0.9216 | 0.9333 | 0.9589 | 0.8276 | 0.8889 | 0.9459 | 0.8571 | 0.8932 | 0.8630 |
| 0.349 | 0.0789 | 35 | 0.3014 | 0.9118 | 0.9211 | 0.9589 | 0.7931 | 0.8846 | 0.9396 | 0.8364 | 0.8760 | 0.8803 |
| 0.3483 | 0.0901 | 40 | 0.2888 | 0.9118 | 0.9571 | 0.9178 | 0.8966 | 0.8125 | 0.9371 | 0.8525 | 0.9072 | 0.8864 |
| 0.3461 | 0.1014 | 45 | 0.2819 | 0.8627 | 0.9538 | 0.8493 | 0.8966 | 0.7027 | 0.8986 | 0.7879 | 0.8729 | 0.8824 |
| 0.3105 | 0.1126 | 50 | 0.2557 | 0.8627 | 0.9538 | 0.8493 | 0.8966 | 0.7027 | 0.8986 | 0.7879 | 0.8729 | 0.8845 |
| 0.2924 | 0.1239 | 55 | 0.2360 | 0.8824 | 0.9841 | 0.8493 | 0.9655 | 0.7179 | 0.9118 | 0.8235 | 0.9074 | 0.8977 |
| 0.3195 | 0.1352 | 60 | 0.2403 | 0.8824 | 0.9841 | 0.8493 | 0.9655 | 0.7179 | 0.9118 | 0.8235 | 0.9074 | 0.9145 |
| 0.3174 | 0.1464 | 65 | 0.2155 | 0.9216 | 0.9851 | 0.9041 | 0.9655 | 0.8 | 0.9429 | 0.875 | 0.9348 | 0.8970 |
| 0.3069 | 0.1577 | 70 | 0.2296 | 0.9020 | 0.9846 | 0.8767 | 0.9655 | 0.7568 | 0.9275 | 0.8485 | 0.9211 | 0.8902 |
| 0.2821 | 0.1690 | 75 | 0.2621 | 0.8725 | 0.9839 | 0.8356 | 0.9655 | 0.7 | 0.9037 | 0.8116 | 0.9006 | 0.8890 |
| 0.2904 | 0.1802 | 80 | 0.2365 | 0.8922 | 0.9844 | 0.8630 | 0.9655 | 0.7368 | 0.9197 | 0.8358 | 0.9143 | 0.8940 |
| 0.226 | 0.1915 | 85 | 0.2097 | 0.9216 | 0.9851 | 0.9041 | 0.9655 | 0.8 | 0.9429 | 0.875 | 0.9348 | 0.9027 |
| 0.2534 | 0.2028 | 90 | 0.2241 | 0.8824 | 0.9841 | 0.8493 | 0.9655 | 0.7179 | 0.9118 | 0.8235 | 0.9074 | 0.9192 |
| 0.2278 | 0.2140 | 95 | 0.2197 | 0.9020 | 0.9846 | 0.8767 | 0.9655 | 0.7568 | 0.9275 | 0.8485 | 0.9211 | 0.8977 |
| 0.198 | 0.2253 | 100 | 0.2201 | 0.8824 | 0.9420 | 0.8904 | 0.8621 | 0.7576 | 0.9155 | 0.8065 | 0.8762 | 0.8904 |
| 0.2287 | 0.2366 | 105 | 0.2341 | 0.8922 | 0.9844 | 0.8630 | 0.9655 | 0.7368 | 0.9197 | 0.8358 | 0.9143 | 0.9140 |
| 0.2597 | 0.2478 | 110 | 0.2366 | 0.8824 | 0.9841 | 0.8493 | 0.9655 | 0.7179 | 0.9118 | 0.8235 | 0.9074 | 0.9280 |
| 0.2479 | 0.2591 | 115 | 0.2153 | 0.9118 | 0.9706 | 0.9041 | 0.9310 | 0.7941 | 0.9362 | 0.8571 | 0.9176 | 0.9315 |
| 0.232 | 0.2703 | 120 | 0.2051 | 0.9020 | 0.9565 | 0.9041 | 0.8966 | 0.7879 | 0.9296 | 0.8387 | 0.9003 | 0.9339 |
| 0.2441 | 0.2816 | 125 | 0.2070 | 0.9118 | 0.9706 | 0.9041 | 0.9310 | 0.7941 | 0.9362 | 0.8571 | 0.9176 | 0.9407 |
| 0.2062 | 0.2929 | 130 | 0.2096 | 0.9020 | 0.9846 | 0.8767 | 0.9655 | 0.7568 | 0.9275 | 0.8485 | 0.9211 | 0.9433 |
| 0.2558 | 0.3041 | 135 | 0.1993 | 0.9020 | 0.9846 | 0.8767 | 0.9655 | 0.7568 | 0.9275 | 0.8485 | 0.9211 | 0.9466 |
| 0.2381 | 0.3154 | 140 | 0.1867 | 0.9118 | 0.9571 | 0.9178 | 0.8966 | 0.8125 | 0.9371 | 0.8525 | 0.9072 | 0.9447 |
| 0.2106 | 0.3267 | 145 | 0.2004 | 0.9118 | 0.9706 | 0.9041 | 0.9310 | 0.7941 | 0.9362 | 0.8571 | 0.9176 | 0.9419 |
| 0.2474 | 0.3379 | 150 | 0.2106 | 0.8922 | 0.9697 | 0.8767 | 0.9310 | 0.75 | 0.9209 | 0.8308 | 0.9039 | 0.9428 |
| 0.2377 | 0.3492 | 155 | 0.2037 | 0.8922 | 0.9429 | 0.9041 | 0.8621 | 0.7812 | 0.9231 | 0.8197 | 0.8831 | 0.9374 |
| 0.2411 | 0.3605 | 160 | 0.2217 | 0.9020 | 0.9846 | 0.8767 | 0.9655 | 0.7568 | 0.9275 | 0.8485 | 0.9211 | 0.9485 |
| 0.2158 | 0.3717 | 165 | 0.2097 | 0.9020 | 0.9565 | 0.9041 | 0.8966 | 0.7879 | 0.9296 | 0.8387 | 0.9003 | 0.9400 |
| 0.2489 | 0.3830 | 170 | 0.2116 | 0.9020 | 0.9701 | 0.8904 | 0.9310 | 0.7714 | 0.9286 | 0.8438 | 0.9107 | 0.9421 |
| 0.2406 | 0.3943 | 175 | 0.2371 | 0.8922 | 0.9844 | 0.8630 | 0.9655 | 0.7368 | 0.9197 | 0.8358 | 0.9143 | 0.9445 |
| 0.2038 | 0.4055 | 180 | 0.2064 | 0.9216 | 0.9851 | 0.9041 | 0.9655 | 0.8 | 0.9429 | 0.875 | 0.9348 | 0.9490 |
| 0.2539 | 0.4168 | 185 | 0.1864 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9405 |
| 0.2583 | 0.4280 | 190 | 0.2180 | 0.8922 | 0.9844 | 0.8630 | 0.9655 | 0.7368 | 0.9197 | 0.8358 | 0.9143 | 0.9410 |
| 0.24 | 0.4393 | 195 | 0.2054 | 0.9118 | 0.9706 | 0.9041 | 0.9310 | 0.7941 | 0.9362 | 0.8571 | 0.9176 | 0.9339 |
| 0.1977 | 0.4506 | 200 | 0.2223 | 0.8824 | 0.9692 | 0.8630 | 0.9310 | 0.7297 | 0.9130 | 0.8182 | 0.8970 | 0.9343 |
| 0.1992 | 0.4618 | 205 | 0.2221 | 0.8922 | 0.9844 | 0.8630 | 0.9655 | 0.7368 | 0.9197 | 0.8358 | 0.9143 | 0.9395 |
| 0.2732 | 0.4731 | 210 | 0.1947 | 0.9216 | 0.9851 | 0.9041 | 0.9655 | 0.8 | 0.9429 | 0.875 | 0.9348 | 0.9490 |
| 0.2074 | 0.4844 | 215 | 0.1795 | 0.9412 | 0.9855 | 0.9315 | 0.9655 | 0.8485 | 0.9577 | 0.9032 | 0.9485 | 0.9495 |
| 0.2161 | 0.4956 | 220 | 0.2092 | 0.9020 | 0.9846 | 0.8767 | 0.9655 | 0.7568 | 0.9275 | 0.8485 | 0.9211 | 0.9544 |
| 0.2013 | 0.5069 | 225 | 0.2009 | 0.9020 | 0.9846 | 0.8767 | 0.9655 | 0.7568 | 0.9275 | 0.8485 | 0.9211 | 0.9539 |
| 0.278 | 0.5182 | 230 | 0.1866 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9499 |
| 0.2042 | 0.5294 | 235 | 0.2101 | 0.8824 | 0.9841 | 0.8493 | 0.9655 | 0.7179 | 0.9118 | 0.8235 | 0.9074 | 0.9565 |
| 0.2298 | 0.5407 | 240 | 0.2051 | 0.8922 | 0.9844 | 0.8630 | 0.9655 | 0.7368 | 0.9197 | 0.8358 | 0.9143 | 0.9561 |
| 0.1887 | 0.5520 | 245 | 0.1976 | 0.9118 | 0.9848 | 0.8904 | 0.9655 | 0.7778 | 0.9353 | 0.8615 | 0.9280 | 0.9499 |
| 0.2529 | 0.5632 | 250 | 0.1923 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9438 |
| 0.2241 | 0.5745 | 255 | 0.2032 | 0.8922 | 0.9844 | 0.8630 | 0.9655 | 0.7368 | 0.9197 | 0.8358 | 0.9143 | 0.9497 |
| 0.1916 | 0.5858 | 260 | 0.1981 | 0.9020 | 0.9846 | 0.8767 | 0.9655 | 0.7568 | 0.9275 | 0.8485 | 0.9211 | 0.9499 |
| 0.21 | 0.5970 | 265 | 0.2020 | 0.9020 | 0.9846 | 0.8767 | 0.9655 | 0.7568 | 0.9275 | 0.8485 | 0.9211 | 0.9513 |
| 0.2351 | 0.6083 | 270 | 0.1986 | 0.9020 | 0.9846 | 0.8767 | 0.9655 | 0.7568 | 0.9275 | 0.8485 | 0.9211 | 0.9469 |
| 0.1987 | 0.6195 | 275 | 0.2003 | 0.9020 | 0.9846 | 0.8767 | 0.9655 | 0.7568 | 0.9275 | 0.8485 | 0.9211 | 0.9445 |
| 0.2225 | 0.6308 | 280 | 0.1998 | 0.9118 | 0.9848 | 0.8904 | 0.9655 | 0.7778 | 0.9353 | 0.8615 | 0.9280 | 0.9443 |
| 0.2113 | 0.6421 | 285 | 0.1917 | 0.9118 | 0.9571 | 0.9178 | 0.8966 | 0.8125 | 0.9371 | 0.8525 | 0.9072 | 0.9457 |
| 0.2216 | 0.6533 | 290 | 0.1924 | 0.9020 | 0.9565 | 0.9041 | 0.8966 | 0.7879 | 0.9296 | 0.8387 | 0.9003 | 0.9469 |
| 0.2501 | 0.6646 | 295 | 0.1962 | 0.9118 | 0.9706 | 0.9041 | 0.9310 | 0.7941 | 0.9362 | 0.8571 | 0.9176 | 0.9499 |
| 0.2362 | 0.6759 | 300 | 0.1966 | 0.9118 | 0.9848 | 0.8904 | 0.9655 | 0.7778 | 0.9353 | 0.8615 | 0.9280 | 0.9556 |
| 0.2129 | 0.6871 | 305 | 0.1958 | 0.9118 | 0.9848 | 0.8904 | 0.9655 | 0.7778 | 0.9353 | 0.8615 | 0.9280 | 0.9542 |
| 0.186 | 0.6984 | 310 | 0.1857 | 0.9216 | 0.9577 | 0.9315 | 0.8966 | 0.8387 | 0.9444 | 0.8667 | 0.9140 | 0.9537 |
| 0.2212 | 0.7097 | 315 | 0.1817 | 0.9216 | 0.9577 | 0.9315 | 0.8966 | 0.8387 | 0.9444 | 0.8667 | 0.9140 | 0.9532 |
| 0.2028 | 0.7209 | 320 | 0.1813 | 0.9216 | 0.9577 | 0.9315 | 0.8966 | 0.8387 | 0.9444 | 0.8667 | 0.9140 | 0.9535 |
| 0.1866 | 0.7322 | 325 | 0.1849 | 0.9314 | 0.9714 | 0.9315 | 0.9310 | 0.8438 | 0.9510 | 0.8852 | 0.9313 | 0.9561 |
| 0.2064 | 0.7435 | 330 | 0.1925 | 0.9314 | 0.9853 | 0.9178 | 0.9655 | 0.8235 | 0.9504 | 0.8889 | 0.9417 | 0.9561 |
| 0.2209 | 0.7547 | 335 | 0.1945 | 0.9314 | 0.9853 | 0.9178 | 0.9655 | 0.8235 | 0.9504 | 0.8889 | 0.9417 | 0.9547 |
| 0.2315 | 0.7660 | 340 | 0.1870 | 0.9314 | 0.9714 | 0.9315 | 0.9310 | 0.8438 | 0.9510 | 0.8852 | 0.9313 | 0.9547 |
| 0.2652 | 0.7772 | 345 | 0.1865 | 0.9216 | 0.9577 | 0.9315 | 0.8966 | 0.8387 | 0.9444 | 0.8667 | 0.9140 | 0.9530 |
| 0.2637 | 0.7885 | 350 | 0.1898 | 0.9314 | 0.9714 | 0.9315 | 0.9310 | 0.8438 | 0.9510 | 0.8852 | 0.9313 | 0.9525 |
| 0.237 | 0.7998 | 355 | 0.1956 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9518 |
| 0.1956 | 0.8110 | 360 | 0.2010 | 0.9314 | 0.9853 | 0.9178 | 0.9655 | 0.8235 | 0.9504 | 0.8889 | 0.9417 | 0.9513 |
| 0.2379 | 0.8223 | 365 | 0.2027 | 0.9216 | 0.9851 | 0.9041 | 0.9655 | 0.8 | 0.9429 | 0.875 | 0.9348 | 0.9523 |
| 0.2119 | 0.8336 | 370 | 0.2027 | 0.9314 | 0.9853 | 0.9178 | 0.9655 | 0.8235 | 0.9504 | 0.8889 | 0.9417 | 0.9499 |
| 0.2032 | 0.8448 | 375 | 0.2001 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9490 |
| 0.2422 | 0.8561 | 380 | 0.1990 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9478 |
| 0.2829 | 0.8674 | 385 | 0.1985 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9502 |
| 0.2246 | 0.8786 | 390 | 0.1984 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9483 |
| 0.1988 | 0.8899 | 395 | 0.1978 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9487 |
| 0.1628 | 0.9012 | 400 | 0.1978 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9504 |
| 0.1933 | 0.9124 | 405 | 0.1983 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9495 |
| 0.2364 | 0.9237 | 410 | 0.1983 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9497 |
| 0.1937 | 0.9349 | 415 | 0.1979 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9495 |
| 0.2002 | 0.9462 | 420 | 0.1980 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9497 |
| 0.1955 | 0.9575 | 425 | 0.1979 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9487 |
| 0.2134 | 0.9687 | 430 | 0.1973 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9495 |
| 0.1779 | 0.9800 | 435 | 0.1969 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9499 |
| 0.2254 | 0.9913 | 440 | 0.1986 | 0.9216 | 0.9710 | 0.9178 | 0.9310 | 0.8182 | 0.9437 | 0.8710 | 0.9244 | 0.9502 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.0
- Pytorch 2.4.0+cu118
- Datasets 3.0.0
- Tokenizers 0.20.1 |