UTI_L3_1000steps_1e7rate_05beta_CSFTDPO
This model is a fine-tuned version of tsavage68/UTI_L3_1000steps_1e5rate_SFT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0164
- Rewards/chosen: 1.6699
- Rewards/rejected: -6.1458
- Rewards/accuracies: 0.9900
- Rewards/margins: 7.8157
- Logps/rejected: -75.4864
- Logps/chosen: -29.1393
- Logits/rejected: -1.3321
- Logits/chosen: -1.3145
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-07
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6936 | 0.3333 | 25 | 0.6887 | -0.0007 | -0.0109 | 0.5300 | 0.0102 | -63.2166 | -32.4804 | -1.3231 | -1.3079 |
| 0.6544 | 0.6667 | 50 | 0.6317 | 0.0212 | -0.1104 | 0.8500 | 0.1316 | -63.4155 | -32.4367 | -1.3229 | -1.3078 |
| 0.5537 | 1.0 | 75 | 0.5050 | 0.0832 | -0.3693 | 0.9400 | 0.4525 | -63.9333 | -32.3125 | -1.3234 | -1.3083 |
| 0.3404 | 1.3333 | 100 | 0.3397 | 0.1907 | -0.8797 | 0.9800 | 1.0704 | -64.9540 | -32.0976 | -1.3239 | -1.3089 |
| 0.2191 | 1.6667 | 125 | 0.2217 | 0.3556 | -1.4579 | 0.9900 | 1.8135 | -66.1104 | -31.7678 | -1.3246 | -1.3095 |
| 0.1721 | 2.0 | 150 | 0.1545 | 0.5057 | -1.8983 | 0.9900 | 2.4040 | -66.9912 | -31.4675 | -1.3248 | -1.3097 |
| 0.0763 | 2.3333 | 175 | 0.1116 | 0.6367 | -2.3670 | 0.9900 | 3.0037 | -67.9287 | -31.2056 | -1.3255 | -1.3103 |
| 0.0669 | 2.6667 | 200 | 0.0818 | 0.7555 | -2.7499 | 0.9900 | 3.5054 | -68.6945 | -30.9681 | -1.3264 | -1.3111 |
| 0.0388 | 3.0 | 225 | 0.0620 | 0.8673 | -3.2396 | 0.9900 | 4.1068 | -69.6738 | -30.7445 | -1.3267 | -1.3113 |
| 0.0653 | 3.3333 | 250 | 0.0506 | 0.9617 | -3.6047 | 0.9900 | 4.5664 | -70.4041 | -30.5557 | -1.3274 | -1.3119 |
| 0.0332 | 3.6667 | 275 | 0.0406 | 1.0595 | -4.0208 | 0.9900 | 5.0803 | -71.2363 | -30.3600 | -1.3276 | -1.3119 |
| 0.0522 | 4.0 | 300 | 0.0339 | 1.1423 | -4.3687 | 0.9900 | 5.5110 | -71.9320 | -30.1943 | -1.3282 | -1.3123 |
| 0.005 | 4.3333 | 325 | 0.0293 | 1.2385 | -4.6734 | 0.9900 | 5.9119 | -72.5414 | -30.0020 | -1.3286 | -1.3124 |
| 0.0284 | 4.6667 | 350 | 0.0256 | 1.3119 | -4.9072 | 0.9900 | 6.2191 | -73.0091 | -29.8553 | -1.3295 | -1.3132 |
| 0.0393 | 5.0 | 375 | 0.0229 | 1.3864 | -5.1293 | 0.9900 | 6.5157 | -73.4534 | -29.7063 | -1.3298 | -1.3132 |
| 0.0261 | 5.3333 | 400 | 0.0214 | 1.4513 | -5.3049 | 0.9900 | 6.7563 | -73.8046 | -29.5763 | -1.3302 | -1.3135 |
| 0.0403 | 5.6667 | 425 | 0.0204 | 1.4964 | -5.4655 | 0.9900 | 6.9619 | -74.1256 | -29.4862 | -1.3304 | -1.3136 |
| 0.0197 | 6.0 | 450 | 0.0190 | 1.5233 | -5.6170 | 0.9900 | 7.1404 | -74.4287 | -29.4324 | -1.3307 | -1.3137 |
| 0.0023 | 6.3333 | 475 | 0.0186 | 1.5672 | -5.7288 | 0.9900 | 7.2960 | -74.6523 | -29.3447 | -1.3310 | -1.3139 |
| 0.0391 | 6.6667 | 500 | 0.0181 | 1.5895 | -5.8057 | 0.9900 | 7.3952 | -74.8060 | -29.2999 | -1.3313 | -1.3141 |
| 0.0044 | 7.0 | 525 | 0.0174 | 1.6125 | -5.9110 | 0.9900 | 7.5235 | -75.0167 | -29.2541 | -1.3314 | -1.3141 |
| 0.0034 | 7.3333 | 550 | 0.0178 | 1.6265 | -5.9426 | 0.9900 | 7.5691 | -75.0799 | -29.2260 | -1.3316 | -1.3143 |
| 0.0214 | 7.6667 | 575 | 0.0167 | 1.6348 | -6.0154 | 0.9900 | 7.6502 | -75.2254 | -29.2094 | -1.3316 | -1.3143 |
| 0.0363 | 8.0 | 600 | 0.0166 | 1.6397 | -6.0402 | 0.9900 | 7.6798 | -75.2751 | -29.1997 | -1.3318 | -1.3144 |
| 0.0366 | 8.3333 | 625 | 0.0168 | 1.6498 | -6.0578 | 0.9900 | 7.7076 | -75.3102 | -29.1794 | -1.3320 | -1.3145 |
| 0.0011 | 8.6667 | 650 | 0.0168 | 1.6607 | -6.0845 | 0.9900 | 7.7452 | -75.3637 | -29.1576 | -1.3319 | -1.3145 |
| 0.0043 | 9.0 | 675 | 0.0167 | 1.6659 | -6.1131 | 0.9900 | 7.7790 | -75.4209 | -29.1472 | -1.3321 | -1.3146 |
| 0.0197 | 9.3333 | 700 | 0.0161 | 1.6703 | -6.1301 | 0.9900 | 7.8004 | -75.4550 | -29.1385 | -1.3320 | -1.3145 |
| 0.0186 | 9.6667 | 725 | 0.0165 | 1.6713 | -6.1341 | 0.9900 | 7.8054 | -75.4628 | -29.1364 | -1.3321 | -1.3147 |
| 0.0039 | 10.0 | 750 | 0.0165 | 1.6700 | -6.1407 | 0.9900 | 7.8106 | -75.4760 | -29.1391 | -1.3321 | -1.3146 |
| 0.0005 | 10.3333 | 775 | 0.0164 | 1.6769 | -6.1401 | 0.9900 | 7.8170 | -75.4749 | -29.1251 | -1.3321 | -1.3146 |
| 0.0185 | 10.6667 | 800 | 0.0164 | 1.6763 | -6.1561 | 0.9900 | 7.8324 | -75.5069 | -29.1265 | -1.3322 | -1.3146 |
| 0.0212 | 11.0 | 825 | 0.0162 | 1.6734 | -6.1441 | 0.9900 | 7.8175 | -75.4828 | -29.1321 | -1.3322 | -1.3145 |
| 0.0011 | 11.3333 | 850 | 0.0159 | 1.6707 | -6.1474 | 0.9900 | 7.8181 | -75.4894 | -29.1376 | -1.3321 | -1.3145 |
| 0.0361 | 11.6667 | 875 | 0.0165 | 1.6746 | -6.1464 | 0.9900 | 7.8209 | -75.4874 | -29.1299 | -1.3322 | -1.3147 |
| 0.0029 | 12.0 | 900 | 0.0161 | 1.6773 | -6.1406 | 0.9900 | 7.8179 | -75.4759 | -29.1244 | -1.3321 | -1.3146 |
| 0.019 | 12.3333 | 925 | 0.0163 | 1.6716 | -6.1497 | 0.9900 | 7.8213 | -75.4941 | -29.1358 | -1.3321 | -1.3146 |
| 0.0204 | 12.6667 | 950 | 0.0164 | 1.6699 | -6.1458 | 0.9900 | 7.8157 | -75.4864 | -29.1393 | -1.3321 | -1.3145 |
| 0.0395 | 13.0 | 975 | 0.0164 | 1.6699 | -6.1458 | 0.9900 | 7.8157 | -75.4864 | -29.1393 | -1.3321 | -1.3145 |
| 0.0048 | 13.3333 | 1000 | 0.0164 | 1.6699 | -6.1458 | 0.9900 | 7.8157 | -75.4864 | -29.1393 | -1.3321 | -1.3145 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.0+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1
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Model tree for tsavage68/UTI_L3_1000steps_1e7rate_05beta_CSFTDPO
Base model
meta-llama/Meta-Llama-3-8B-Instruct
Finetuned
tsavage68/UTI_L3_1000steps_1e5rate_SFT