PE-12b-pythia
This model is a fine-tuned version of EleutherAI/pythia-12b-deduped on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1421
- Rewards/chosen: 3.5045
- Rewards/rejected: -2.3171
- Rewards/accuracies: 0.9441
- Rewards/margins: 5.8216
- Logps/rejected: -95.5639
- Logps/chosen: -116.1507
- Logits/rejected: -0.4604
- Logits/chosen: -0.4355
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: 3e-07
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.8825 | 0.05 | 100 | 0.8872 | 0.1884 | 0.1204 | 0.5056 | 0.0680 | -90.6889 | -122.7830 | -0.5017 | -0.4522 |
| 0.9136 | 0.09 | 200 | 0.8325 | 0.3253 | 0.0714 | 0.5894 | 0.2540 | -90.7870 | -122.5091 | -0.4960 | -0.4447 |
| 0.7507 | 0.14 | 300 | 0.7816 | 0.5741 | 0.2797 | 0.5670 | 0.2944 | -90.3703 | -122.0116 | -0.4909 | -0.4426 |
| 0.6142 | 0.18 | 400 | 0.6435 | 1.0753 | 0.4404 | 0.6369 | 0.6348 | -90.0489 | -121.0092 | -0.4793 | -0.4322 |
| 0.519 | 0.23 | 500 | 0.5196 | 1.7213 | 0.5624 | 0.7430 | 1.1590 | -89.8050 | -119.7171 | -0.4559 | -0.4084 |
| 0.4858 | 0.27 | 600 | 0.4351 | 2.2085 | 0.5923 | 0.7877 | 1.6162 | -89.7450 | -118.7428 | -0.4592 | -0.4138 |
| 0.4048 | 0.32 | 700 | 0.3878 | 2.6105 | 0.5736 | 0.8324 | 2.0369 | -89.7825 | -117.9388 | -0.4398 | -0.3953 |
| 0.3623 | 0.37 | 800 | 0.3383 | 2.7055 | 0.4610 | 0.8520 | 2.2446 | -90.0078 | -117.7487 | -0.4492 | -0.4046 |
| 0.308 | 0.41 | 900 | 0.3145 | 2.9742 | 0.3506 | 0.8520 | 2.6236 | -90.2285 | -117.2114 | -0.4381 | -0.3971 |
| 0.3092 | 0.46 | 1000 | 0.3125 | 3.1541 | 0.2687 | 0.8352 | 2.8854 | -90.3922 | -116.8515 | -0.4276 | -0.3926 |
| 0.2765 | 0.5 | 1100 | 0.2939 | 3.1208 | 0.1475 | 0.8603 | 2.9733 | -90.6347 | -116.9181 | -0.4615 | -0.4216 |
| 0.3058 | 0.55 | 1200 | 0.2772 | 2.9861 | -0.1371 | 0.8771 | 3.1232 | -91.2038 | -117.1875 | -0.4249 | -0.3887 |
| 0.2702 | 0.59 | 1300 | 0.2592 | 3.3217 | -0.0639 | 0.8715 | 3.3856 | -91.0574 | -116.5163 | -0.4497 | -0.4113 |
| 0.2316 | 0.64 | 1400 | 0.2491 | 3.3560 | -0.2934 | 0.8855 | 3.6494 | -91.5165 | -116.4477 | -0.4234 | -0.3869 |
| 0.2344 | 0.68 | 1500 | 0.2506 | 3.2223 | -0.2242 | 0.8687 | 3.4464 | -91.3780 | -116.7152 | -0.4515 | -0.4151 |
| 0.2332 | 0.73 | 1600 | 0.2350 | 3.2137 | -0.4070 | 0.8855 | 3.6207 | -91.7436 | -116.7324 | -0.4299 | -0.3936 |
| 0.2258 | 0.78 | 1700 | 0.2477 | 3.0894 | -0.5590 | 0.8939 | 3.6484 | -92.0476 | -116.9809 | -0.4316 | -0.3960 |
| 0.2526 | 0.82 | 1800 | 0.2277 | 3.2845 | -0.5527 | 0.8771 | 3.8373 | -92.0351 | -116.5907 | -0.4420 | -0.4076 |
| 0.2025 | 0.87 | 1900 | 0.2182 | 3.2061 | -0.8100 | 0.9022 | 4.0160 | -92.5496 | -116.7476 | -0.4319 | -0.3974 |
| 0.2253 | 0.91 | 2000 | 0.2149 | 3.2765 | -0.9756 | 0.9078 | 4.2521 | -92.8809 | -116.6067 | -0.4391 | -0.4023 |
| 0.2084 | 0.96 | 2100 | 0.2223 | 3.1160 | -1.0659 | 0.8939 | 4.1820 | -93.0615 | -116.9277 | -0.4283 | -0.3954 |
| 0.1896 | 1.0 | 2200 | 0.2100 | 3.1835 | -1.0131 | 0.8911 | 4.1966 | -92.9559 | -116.7927 | -0.4517 | -0.4154 |
| 0.2294 | 1.05 | 2300 | 0.2070 | 3.1205 | -1.0873 | 0.8939 | 4.2078 | -93.1043 | -116.9187 | -0.4412 | -0.4051 |
| 0.1897 | 1.1 | 2400 | 0.2011 | 3.1553 | -1.0875 | 0.9050 | 4.2428 | -93.1047 | -116.8492 | -0.4483 | -0.4136 |
| 0.1943 | 1.14 | 2500 | 0.1953 | 3.3317 | -1.2261 | 0.9022 | 4.5578 | -93.3819 | -116.4964 | -0.4488 | -0.4137 |
| 0.1749 | 1.19 | 2600 | 0.1975 | 3.2186 | -1.3232 | 0.8911 | 4.5419 | -93.5761 | -116.7225 | -0.4500 | -0.4160 |
| 0.1881 | 1.23 | 2700 | 0.1838 | 3.3207 | -1.3323 | 0.9274 | 4.6530 | -93.5944 | -116.5184 | -0.4262 | -0.3962 |
| 0.1611 | 1.28 | 2800 | 0.1833 | 3.2881 | -1.3588 | 0.9106 | 4.6469 | -93.6472 | -116.5835 | -0.4404 | -0.4091 |
| 0.1653 | 1.32 | 2900 | 0.1959 | 3.2545 | -1.6143 | 0.9190 | 4.8688 | -94.1584 | -116.6508 | -0.4252 | -0.3996 |
| 0.1613 | 1.37 | 3000 | 0.1779 | 3.3926 | -1.5190 | 0.9218 | 4.9117 | -93.9678 | -116.3744 | -0.4374 | -0.4071 |
| 0.1785 | 1.42 | 3100 | 0.1840 | 3.4053 | -1.6286 | 0.9246 | 5.0339 | -94.1868 | -116.3491 | -0.4280 | -0.3987 |
| 0.1544 | 1.46 | 3200 | 0.1686 | 3.5029 | -1.6389 | 0.9218 | 5.1418 | -94.2075 | -116.1539 | -0.4624 | -0.4309 |
| 0.1492 | 1.51 | 3300 | 0.1706 | 3.2854 | -1.8094 | 0.9330 | 5.0948 | -94.5485 | -116.5889 | -0.4148 | -0.3943 |
| 0.1719 | 1.55 | 3400 | 0.1691 | 3.5148 | -1.7457 | 0.9274 | 5.2605 | -94.4210 | -116.1301 | -0.4542 | -0.4253 |
| 0.1905 | 1.6 | 3500 | 0.1719 | 3.4941 | -1.7454 | 0.9246 | 5.2395 | -94.4204 | -116.1715 | -0.4479 | -0.4189 |
| 0.1354 | 1.64 | 3600 | 0.1749 | 3.5351 | -1.7024 | 0.9106 | 5.2375 | -94.3345 | -116.0895 | -0.4608 | -0.4303 |
| 0.1644 | 1.69 | 3700 | 0.1597 | 3.5736 | -1.6580 | 0.9246 | 5.2316 | -94.2457 | -116.0126 | -0.4469 | -0.4192 |
| 0.1598 | 1.73 | 3800 | 0.1613 | 3.6646 | -1.7035 | 0.9078 | 5.3681 | -94.3367 | -115.8306 | -0.4631 | -0.4349 |
| 0.1337 | 1.78 | 3900 | 0.1583 | 3.5502 | -1.8444 | 0.9134 | 5.3946 | -94.6184 | -116.0593 | -0.4658 | -0.4368 |
| 0.1534 | 1.83 | 4000 | 0.1572 | 3.5076 | -1.9137 | 0.9190 | 5.4213 | -94.7571 | -116.1446 | -0.4610 | -0.4328 |
| 0.1327 | 1.87 | 4100 | 0.1607 | 3.5711 | -1.9143 | 0.9218 | 5.4854 | -94.7583 | -116.0175 | -0.4404 | -0.4153 |
| 0.162 | 1.92 | 4200 | 0.1565 | 3.4852 | -2.0136 | 0.9330 | 5.4988 | -94.9568 | -116.1893 | -0.4641 | -0.4373 |
| 0.1471 | 1.96 | 4300 | 0.1524 | 3.5639 | -1.9766 | 0.9246 | 5.5406 | -94.8830 | -116.0319 | -0.4627 | -0.4338 |
| 0.1333 | 2.01 | 4400 | 0.1418 | 3.6173 | -1.9710 | 0.9162 | 5.5883 | -94.8717 | -115.9251 | -0.4608 | -0.4328 |
| 0.13 | 2.05 | 4500 | 0.1485 | 3.6275 | -1.9865 | 0.9358 | 5.6140 | -94.9027 | -115.9047 | -0.4604 | -0.4319 |
| 0.1311 | 2.1 | 4600 | 0.1503 | 3.4735 | -2.1194 | 0.9134 | 5.5928 | -95.1684 | -116.2128 | -0.4405 | -0.4123 |
| 0.1329 | 2.15 | 4700 | 0.1431 | 3.5793 | -2.1059 | 0.9218 | 5.6852 | -95.1415 | -116.0012 | -0.4519 | -0.4229 |
| 0.1346 | 2.19 | 4800 | 0.1494 | 3.6059 | -2.0642 | 0.9274 | 5.6701 | -95.0581 | -115.9479 | -0.4639 | -0.4332 |
| 0.1462 | 2.24 | 4900 | 0.1455 | 3.4721 | -2.1648 | 0.9218 | 5.6369 | -95.2593 | -116.2156 | -0.4553 | -0.4258 |
| 0.1221 | 2.28 | 5000 | 0.1538 | 3.6293 | -2.1472 | 0.9385 | 5.7764 | -95.2240 | -115.9012 | -0.4525 | -0.4268 |
| 0.1329 | 2.33 | 5100 | 0.1486 | 3.4734 | -2.1778 | 0.9358 | 5.6512 | -95.2853 | -116.2130 | -0.4578 | -0.4301 |
| 0.1284 | 2.37 | 5200 | 0.1527 | 3.4805 | -2.1670 | 0.9078 | 5.6474 | -95.2636 | -116.1988 | -0.4611 | -0.4329 |
| 0.1238 | 2.42 | 5300 | 0.1433 | 3.4570 | -2.1768 | 0.9274 | 5.6338 | -95.2832 | -116.2457 | -0.4451 | -0.4191 |
| 0.1317 | 2.46 | 5400 | 0.1421 | 3.5647 | -2.2232 | 0.9330 | 5.7880 | -95.3761 | -116.0303 | -0.4565 | -0.4342 |
| 0.131 | 2.51 | 5500 | 0.1478 | 3.4211 | -2.2681 | 0.9190 | 5.6892 | -95.4659 | -116.3175 | -0.4444 | -0.4147 |
| 0.1235 | 2.56 | 5600 | 0.1428 | 3.5292 | -2.2798 | 0.9413 | 5.8089 | -95.4892 | -116.1014 | -0.4485 | -0.4234 |
| 0.1122 | 2.6 | 5700 | 0.1445 | 3.6102 | -2.2363 | 0.9330 | 5.8465 | -95.4023 | -115.9393 | -0.4473 | -0.4233 |
| 0.1172 | 2.65 | 5800 | 0.1415 | 3.5813 | -2.1899 | 0.9246 | 5.7712 | -95.3095 | -115.9972 | -0.4648 | -0.4357 |
| 0.1257 | 2.69 | 5900 | 0.1428 | 3.4075 | -2.3047 | 0.9218 | 5.7122 | -95.5390 | -116.3447 | -0.4553 | -0.4269 |
| 0.1441 | 2.74 | 6000 | 0.1426 | 3.4287 | -2.3210 | 0.9190 | 5.7497 | -95.5717 | -116.3024 | -0.4673 | -0.4401 |
| 0.1359 | 2.78 | 6100 | 0.1479 | 3.4833 | -2.2993 | 0.9358 | 5.7826 | -95.5282 | -116.1931 | -0.4409 | -0.4173 |
| 0.1332 | 2.83 | 6200 | 0.1442 | 3.4741 | -2.2726 | 0.9330 | 5.7466 | -95.4748 | -116.2116 | -0.4512 | -0.4262 |
| 0.1454 | 2.88 | 6300 | 0.1397 | 3.4410 | -2.2911 | 0.9358 | 5.7320 | -95.5118 | -116.2778 | -0.4604 | -0.4355 |
| 0.1355 | 2.92 | 6400 | 0.1471 | 3.3740 | -2.3739 | 0.9330 | 5.7479 | -95.6775 | -116.4117 | -0.4473 | -0.4225 |
| 0.1114 | 2.97 | 6500 | 0.1397 | 3.4854 | -2.3222 | 0.9302 | 5.8076 | -95.5740 | -116.1889 | -0.4595 | -0.4345 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.1+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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