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OpenELM-1_1B-DPO-full-max-10-reward

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Commit
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Files changed (9) hide show
  1. README.md +37 -37
  2. all_results.json +15 -15
  3. eval_results.json +11 -11
  4. model.safetensors +1 -1
  5. runs/Oct06_14-29-28_xe8545-a100-15/events.out.tfevents.1728230957.xe8545-a100-15.1082351.1 +3 -0
  6. runs/Oct07_05-34-18_xe8545-a100-15/events.out.tfevents.1728272812.xe8545-a100-15.1096845.0 +3 -0
  7. train_results.json +4 -4
  8. trainer_state.json +0 -0
  9. training_args.bin +1 -1
README.md CHANGED
@@ -17,15 +17,15 @@ should probably proofread and complete it, then remove this comment. -->
17
 
18
  This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5774
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- - Rewards/chosen: -11.5
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- - Rewards/rejected: -13.5625
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- - Rewards/accuracies: 0.5879
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- - Rewards/margins: 2.0938
25
- - Logps/rejected: -1648.0
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- - Logps/chosen: -1464.0
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- - Logits/rejected: -0.6484
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- - Logits/chosen: -2.5938
29
 
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  ## Model description
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@@ -62,34 +62,34 @@ The following hyperparameters were used during training:
62
 
63
  | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
64
  |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
65
- | 0.3697 | 0.1047 | 100 | 0.6861 | -2.2656 | -2.5938 | 0.5957 | 0.3242 | -548.0 | -544.0 | -12.875 | -13.1875 |
66
- | 0.2859 | 0.2094 | 200 | 0.7473 | -2.8281 | -3.3281 | 0.5957 | 0.5039 | -620.0 | -600.0 | -7.125 | -7.9062 |
67
- | 0.2457 | 0.3141 | 300 | 0.8945 | -4.25 | -4.8438 | 0.5762 | 0.5781 | -772.0 | -744.0 | -4.875 | -5.875 |
68
- | 0.2779 | 0.4188 | 400 | 0.7848 | -4.6875 | -5.2812 | 0.5996 | 0.5742 | -816.0 | -788.0 | -5.6562 | -6.8125 |
69
- | 0.2378 | 0.5236 | 500 | 0.8630 | -5.4062 | -6.4062 | 0.6016 | 1.0156 | -928.0 | -860.0 | -4.4375 | -5.7188 |
70
- | 0.2478 | 0.6283 | 600 | 0.8302 | -5.4062 | -6.1562 | 0.6270 | 0.7383 | -904.0 | -860.0 | -3.5625 | -4.7812 |
71
- | 0.2346 | 0.7330 | 700 | 0.8088 | -5.1562 | -5.9688 | 0.6211 | 0.8164 | -884.0 | -836.0 | -7.9062 | -9.0 |
72
- | 0.2222 | 0.8377 | 800 | 0.9452 | -6.1562 | -6.9375 | 0.5645 | 0.7734 | -984.0 | -936.0 | -5.6875 | -7.0625 |
73
- | 0.2077 | 0.9424 | 900 | 0.9077 | -6.9688 | -7.7812 | 0.5918 | 0.8125 | -1064.0 | -1016.0 | -6.6562 | -7.75 |
74
- | 0.0616 | 1.0471 | 1000 | 1.1159 | -8.0 | -9.1875 | 0.5879 | 1.1953 | -1208.0 | -1120.0 | -3.4375 | -5.2188 |
75
- | 0.0692 | 1.1518 | 1100 | 1.0924 | -7.5938 | -8.625 | 0.5859 | 1.0469 | -1152.0 | -1080.0 | -4.1875 | -5.6562 |
76
- | 0.0488 | 1.2565 | 1200 | 1.3851 | -11.375 | -12.625 | 0.5938 | 1.2344 | -1552.0 | -1456.0 | -0.3047 | -1.7969 |
77
- | 0.0483 | 1.3613 | 1300 | 1.1343 | -7.875 | -9.0 | 0.6094 | 1.1641 | -1192.0 | -1104.0 | -5.0312 | -6.75 |
78
- | 0.072 | 1.4660 | 1400 | 1.1480 | -8.375 | -9.6875 | 0.6230 | 1.3438 | -1256.0 | -1152.0 | -2.0469 | -3.9844 |
79
- | 0.0465 | 1.5707 | 1500 | 1.3534 | -9.625 | -11.25 | 0.5938 | 1.6016 | -1416.0 | -1280.0 | -2.4375 | -4.375 |
80
- | 0.0541 | 1.6754 | 1600 | 1.1639 | -8.5 | -9.75 | 0.5938 | 1.2266 | -1264.0 | -1168.0 | -3.1719 | -4.9375 |
81
- | 0.0826 | 1.7801 | 1700 | 1.2758 | -9.5 | -11.0 | 0.5977 | 1.4922 | -1392.0 | -1272.0 | -1.8203 | -3.6406 |
82
- | 0.0429 | 1.8848 | 1800 | 1.1922 | -8.5625 | -10.0 | 0.5938 | 1.4375 | -1288.0 | -1176.0 | -1.3672 | -3.3281 |
83
- | 0.0316 | 1.9895 | 1900 | 1.2850 | -9.25 | -10.9375 | 0.5938 | 1.6875 | -1384.0 | -1240.0 | -2.2969 | -4.2188 |
84
- | 0.0026 | 2.0942 | 2000 | 1.4026 | -10.5625 | -12.375 | 0.5957 | 1.7891 | -1528.0 | -1376.0 | -1.0938 | -3.0156 |
85
- | 0.0032 | 2.1990 | 2100 | 1.4889 | -11.0625 | -13.0 | 0.5918 | 1.9297 | -1592.0 | -1424.0 | -0.875 | -2.8281 |
86
- | 0.0059 | 2.3037 | 2200 | 1.5006 | -11.25 | -13.1875 | 0.5996 | 1.9375 | -1608.0 | -1440.0 | -0.8281 | -2.75 |
87
- | 0.008 | 2.4084 | 2300 | 1.5364 | -11.5 | -13.5 | 0.6016 | 1.9688 | -1640.0 | -1472.0 | -0.4961 | -2.4062 |
88
- | 0.0059 | 2.5131 | 2400 | 1.5711 | -11.5 | -13.5 | 0.5898 | 2.0469 | -1640.0 | -1464.0 | -0.6562 | -2.6094 |
89
- | 0.0063 | 2.6178 | 2500 | 1.5534 | -11.375 | -13.4375 | 0.5879 | 2.0469 | -1632.0 | -1456.0 | -0.6367 | -2.5781 |
90
- | 0.0075 | 2.7225 | 2600 | 1.5770 | -11.5625 | -13.625 | 0.5859 | 2.0781 | -1648.0 | -1472.0 | -0.5859 | -2.5312 |
91
- | 0.005 | 2.8272 | 2700 | 1.5729 | -11.4375 | -13.5 | 0.5840 | 2.0938 | -1640.0 | -1464.0 | -0.6562 | -2.6094 |
92
- | 0.0065 | 2.9319 | 2800 | 1.5774 | -11.5 | -13.5625 | 0.5879 | 2.0938 | -1648.0 | -1464.0 | -0.6484 | -2.5938 |
93
 
94
 
95
  ### Framework versions
 
17
 
18
  This model was trained from scratch on an unknown dataset.
19
  It achieves the following results on the evaluation set:
20
+ - Loss: 1.5022
21
+ - Rewards/chosen: -12.0
22
+ - Rewards/rejected: -14.25
23
+ - Rewards/accuracies: 0.5996
24
+ - Rewards/margins: 2.2188
25
+ - Logps/rejected: -1712.0
26
+ - Logps/chosen: -1520.0
27
+ - Logits/rejected: -1.7422
28
+ - Logits/chosen: -3.6875
29
 
30
  ## Model description
31
 
 
62
 
63
  | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
64
  |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
65
+ | 0.3683 | 0.1047 | 100 | 0.6799 | -1.8125 | -2.1719 | 0.6016 | 0.3555 | -506.0 | -500.0 | -12.125 | -12.4375 |
66
+ | 0.2926 | 0.2094 | 200 | 0.7127 | -2.0312 | -2.5156 | 0.6152 | 0.4863 | -540.0 | -520.0 | -10.0 | -10.5625 |
67
+ | 0.2695 | 0.3141 | 300 | 0.7960 | -4.5938 | -5.1562 | 0.5801 | 0.5781 | -804.0 | -776.0 | -7.2812 | -8.1875 |
68
+ | 0.245 | 0.4188 | 400 | 0.7903 | -4.6562 | -5.25 | 0.5801 | 0.5977 | -812.0 | -784.0 | -8.75 | -9.5625 |
69
+ | 0.2375 | 0.5236 | 500 | 0.9612 | -6.75 | -7.875 | 0.6113 | 1.125 | -1080.0 | -992.0 | -7.4688 | -8.6875 |
70
+ | 0.2534 | 0.6283 | 600 | 0.8573 | -5.6562 | -6.5 | 0.6133 | 0.8438 | -940.0 | -884.0 | -8.75 | -9.6875 |
71
+ | 0.2213 | 0.7330 | 700 | 0.8133 | -4.7812 | -5.7188 | 0.6387 | 0.9336 | -860.0 | -796.0 | -5.75 | -7.3125 |
72
+ | 0.2342 | 0.8377 | 800 | 0.8574 | -5.5625 | -6.4688 | 0.6055 | 0.9336 | -936.0 | -872.0 | -7.2812 | -8.5625 |
73
+ | 0.199 | 0.9424 | 900 | 0.8853 | -7.1875 | -8.1875 | 0.6074 | 0.9570 | -1104.0 | -1040.0 | -4.6562 | -6.0938 |
74
+ | 0.0529 | 1.0471 | 1000 | 1.1147 | -8.5 | -9.75 | 0.6055 | 1.2734 | -1264.0 | -1168.0 | -4.4062 | -6.2188 |
75
+ | 0.058 | 1.1518 | 1100 | 1.0443 | -6.25 | -7.25 | 0.5977 | 1.0 | -1012.0 | -940.0 | -7.9375 | -9.1875 |
76
+ | 0.0436 | 1.2565 | 1200 | 1.1756 | -9.5625 | -10.875 | 0.6133 | 1.3438 | -1376.0 | -1272.0 | -1.3125 | -3.0938 |
77
+ | 0.0353 | 1.3613 | 1300 | 1.2987 | -8.75 | -10.4375 | 0.5859 | 1.6875 | -1328.0 | -1192.0 | -5.2812 | -7.0625 |
78
+ | 0.0576 | 1.4660 | 1400 | 1.0486 | -8.0625 | -9.5625 | 0.6172 | 1.4609 | -1240.0 | -1128.0 | -4.625 | -6.4688 |
79
+ | 0.0444 | 1.5707 | 1500 | 1.1459 | -8.875 | -10.5 | 0.6113 | 1.6484 | -1344.0 | -1208.0 | -1.9141 | -3.9219 |
80
+ | 0.0475 | 1.6754 | 1600 | 1.1818 | -8.5625 | -10.125 | 0.5918 | 1.5547 | -1304.0 | -1176.0 | -2.5938 | -4.5625 |
81
+ | 0.0644 | 1.7801 | 1700 | 1.2222 | -9.625 | -11.25 | 0.6055 | 1.6562 | -1416.0 | -1280.0 | -2.7344 | -4.5938 |
82
+ | 0.0397 | 1.8848 | 1800 | 1.0832 | -7.8125 | -9.375 | 0.6172 | 1.5469 | -1224.0 | -1096.0 | -3.3438 | -5.375 |
83
+ | 0.0254 | 1.9895 | 1900 | 1.1882 | -9.8125 | -11.4375 | 0.6191 | 1.6719 | -1432.0 | -1296.0 | -3.7344 | -5.4688 |
84
+ | 0.0037 | 2.0942 | 2000 | 1.3353 | -11.125 | -13.125 | 0.6133 | 1.9766 | -1600.0 | -1432.0 | -2.5938 | -4.5312 |
85
+ | 0.0048 | 2.1990 | 2100 | 1.5185 | -12.1875 | -14.375 | 0.5996 | 2.2031 | -1728.0 | -1536.0 | -2.7656 | -4.7188 |
86
+ | 0.0045 | 2.3037 | 2200 | 1.5012 | -12.4375 | -14.625 | 0.6133 | 2.1875 | -1752.0 | -1560.0 | -1.75 | -3.6406 |
87
+ | 0.0108 | 2.4084 | 2300 | 1.5281 | -12.3125 | -14.5625 | 0.6074 | 2.2344 | -1744.0 | -1552.0 | -1.8047 | -3.75 |
88
+ | 0.0056 | 2.5131 | 2400 | 1.5154 | -12.125 | -14.3125 | 0.6074 | 2.2188 | -1720.0 | -1528.0 | -1.6797 | -3.625 |
89
+ | 0.0051 | 2.6178 | 2500 | 1.5115 | -12.1875 | -14.4375 | 0.6035 | 2.2188 | -1728.0 | -1536.0 | -1.5234 | -3.4531 |
90
+ | 0.0041 | 2.7225 | 2600 | 1.4846 | -11.8125 | -14.0625 | 0.5938 | 2.2031 | -1696.0 | -1504.0 | -1.8047 | -3.75 |
91
+ | 0.0049 | 2.8272 | 2700 | 1.5020 | -12.0 | -14.25 | 0.5977 | 2.2344 | -1712.0 | -1520.0 | -1.7266 | -3.6719 |
92
+ | 0.0063 | 2.9319 | 2800 | 1.5022 | -12.0 | -14.25 | 0.5996 | 2.2188 | -1712.0 | -1520.0 | -1.7422 | -3.6875 |
93
 
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  ### Framework versions
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