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CharlesLi
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OpenELM-1_1B-DPO-full-least-similar

Text Generation
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openelm
trl
dpo
alignment-handbook
Generated from Trainer
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CharlesLi commited on
Commit
518b852
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1 Parent(s): 536bdce

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Files changed (9) hide show
  1. README.md +37 -37
  2. all_results.json +15 -15
  3. eval_results.json +12 -12
  4. model.safetensors +1 -1
  5. runs/Sep22_19-02-28_xe8545-a100-05/events.out.tfevents.1727038341.xe8545-a100-05.377977.1 +3 -0
  6. runs/Sep23_09-29-20_xe8545-a100-19/events.out.tfevents.1727077824.xe8545-a100-19.125277.0 +3 -0
  7. train_results.json +3 -3
  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: 1.0088
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- - Rewards/chosen: -3.4062
22
- - Rewards/rejected: -3.6406
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- - Rewards/accuracies: 0.5078
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- - Rewards/margins: 0.2354
25
- - Logps/rejected: -652.0
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- - Logps/chosen: -660.0
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- - Logits/rejected: -13.375
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- - Logits/chosen: -13.625
29
 
30
  ## Model description
31
 
@@ -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
- | 0.1864 | 0.1047 | 100 | 0.6764 | -0.4473 | -0.5547 | 0.5410 | 0.1084 | -344.0 | -364.0 | -14.5 | -14.6875 |
66
- | 0.1156 | 0.2094 | 200 | 0.6999 | -0.8008 | -0.8984 | 0.5234 | 0.0991 | -378.0 | -398.0 | -11.4375 | -11.6875 |
67
- | 0.1465 | 0.3141 | 300 | 0.7544 | -1.0547 | -1.1641 | 0.4883 | 0.1079 | -406.0 | -424.0 | -10.9375 | -11.375 |
68
- | 0.1468 | 0.4188 | 400 | 0.7513 | -1.1016 | -1.1328 | 0.4707 | 0.0322 | -402.0 | -428.0 | -15.1875 | -15.25 |
69
- | 0.1267 | 0.5236 | 500 | 0.7808 | -1.4219 | -1.4844 | 0.5176 | 0.0574 | -436.0 | -460.0 | -13.125 | -13.375 |
70
- | 0.1435 | 0.6283 | 600 | 0.8511 | -1.7109 | -1.7422 | 0.5 | 0.0308 | -462.0 | -490.0 | -15.625 | -15.6875 |
71
- | 0.1255 | 0.7330 | 700 | 0.8534 | -1.8438 | -2.0312 | 0.5137 | 0.1797 | -492.0 | -502.0 | -13.125 | -13.5625 |
72
- | 0.1142 | 0.8377 | 800 | 0.8559 | -1.5938 | -1.6406 | 0.4922 | 0.0471 | -452.0 | -478.0 | -11.875 | -12.375 |
73
- | 0.1596 | 0.9424 | 900 | 0.8358 | -2.0469 | -2.0938 | 0.4922 | 0.0510 | -498.0 | -524.0 | -14.875 | -15.0625 |
74
- | 0.0231 | 1.0471 | 1000 | 0.8380 | -1.8828 | -2.0312 | 0.5078 | 0.1406 | -492.0 | -506.0 | -12.0625 | -12.5 |
75
- | 0.0293 | 1.1518 | 1100 | 0.8317 | -2.2656 | -2.3906 | 0.5488 | 0.1328 | -528.0 | -544.0 | -12.4375 | -12.875 |
76
- | 0.0171 | 1.2565 | 1200 | 0.8362 | -2.375 | -2.5156 | 0.5332 | 0.1367 | -540.0 | -556.0 | -12.1875 | -12.625 |
77
- | 0.0174 | 1.3613 | 1300 | 0.8684 | -2.9375 | -3.0938 | 0.5195 | 0.1660 | -600.0 | -612.0 | -11.75 | -12.25 |
78
- | 0.0191 | 1.4660 | 1400 | 0.8702 | -2.6875 | -2.8438 | 0.5156 | 0.1504 | -572.0 | -588.0 | -11.5625 | -12.0 |
79
- | 0.036 | 1.5707 | 1500 | 0.9229 | -2.5781 | -2.7188 | 0.5098 | 0.1348 | -560.0 | -576.0 | -11.3125 | -11.8125 |
80
- | 0.018 | 1.6754 | 1600 | 0.9154 | -2.8281 | -2.9844 | 0.5059 | 0.1523 | -588.0 | -600.0 | -12.4375 | -12.875 |
81
- | 0.0304 | 1.7801 | 1700 | 0.9087 | -2.375 | -2.4531 | 0.4902 | 0.0820 | -536.0 | -556.0 | -13.5 | -13.75 |
82
- | 0.0189 | 1.8848 | 1800 | 0.8959 | -2.6719 | -2.8125 | 0.5039 | 0.1367 | -568.0 | -584.0 | -13.0 | -13.375 |
83
- | 0.0113 | 1.9895 | 1900 | 0.9094 | -2.7812 | -2.9531 | 0.5117 | 0.1738 | -584.0 | -596.0 | -13.375 | -13.625 |
84
- | 0.0013 | 2.0942 | 2000 | 0.9535 | -2.9688 | -3.1875 | 0.5137 | 0.2207 | -608.0 | -616.0 | -13.5 | -13.75 |
85
- | 0.0014 | 2.1990 | 2100 | 0.9798 | -3.1562 | -3.375 | 0.5176 | 0.2285 | -628.0 | -632.0 | -13.3125 | -13.5625 |
86
- | 0.0013 | 2.3037 | 2200 | 0.9978 | -3.3281 | -3.5781 | 0.5137 | 0.2402 | -648.0 | -652.0 | -13.3125 | -13.5625 |
87
- | 0.0011 | 2.4084 | 2300 | 1.0081 | -3.4531 | -3.6875 | 0.5137 | 0.2471 | -660.0 | -664.0 | -13.3125 | -13.5625 |
88
- | 0.0017 | 2.5131 | 2400 | 1.0045 | -3.4219 | -3.6719 | 0.5117 | 0.2461 | -656.0 | -660.0 | -13.3125 | -13.5625 |
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- | 0.0013 | 2.6178 | 2500 | 1.0019 | -3.4062 | -3.6562 | 0.5117 | 0.2432 | -656.0 | -660.0 | -13.3125 | -13.5625 |
90
- | 0.0038 | 2.7225 | 2600 | 1.0071 | -3.4062 | -3.6406 | 0.5059 | 0.2354 | -652.0 | -660.0 | -13.375 | -13.625 |
91
- | 0.0009 | 2.8272 | 2700 | 1.0082 | -3.4062 | -3.6406 | 0.5098 | 0.2363 | -652.0 | -660.0 | -13.375 | -13.625 |
92
- | 0.0011 | 2.9319 | 2800 | 1.0088 | -3.4062 | -3.6406 | 0.5078 | 0.2354 | -652.0 | -660.0 | -13.375 | -13.625 |
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: 1.0609
21
+ - Rewards/chosen: -3.7969
22
+ - Rewards/rejected: -4.0
23
+ - Rewards/accuracies: 0.5
24
+ - Rewards/margins: 0.2148
25
+ - Logps/rejected: -692.0
26
+ - Logps/chosen: -700.0
27
+ - Logits/rejected: -12.9375
28
+ - Logits/chosen: -13.25
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
+ | 0.187 | 0.1047 | 100 | 0.6760 | -0.4492 | -0.5586 | 0.5469 | 0.1084 | -344.0 | -364.0 | -14.5625 | -14.6875 |
66
+ | 0.1162 | 0.2094 | 200 | 0.6879 | -0.7734 | -0.875 | 0.5410 | 0.1016 | -376.0 | -396.0 | -11.6875 | -12.0625 |
67
+ | 0.1436 | 0.3141 | 300 | 0.7670 | -1.6562 | -1.7969 | 0.4941 | 0.1377 | -468.0 | -484.0 | -13.875 | -14.0625 |
68
+ | 0.1461 | 0.4188 | 400 | 0.7442 | -1.0469 | -1.0625 | 0.5039 | 0.0201 | -394.0 | -422.0 | -16.5 | -16.625 |
69
+ | 0.1352 | 0.5236 | 500 | 0.8131 | -1.6406 | -1.7031 | 0.5020 | 0.0630 | -460.0 | -482.0 | -15.5625 | -15.6875 |
70
+ | 0.1507 | 0.6283 | 600 | 0.8542 | -1.625 | -1.6328 | 0.4766 | 0.0096 | -452.0 | -482.0 | -17.25 | -17.375 |
71
+ | 0.1278 | 0.7330 | 700 | 0.8274 | -1.7891 | -1.9453 | 0.4980 | 0.1592 | -484.0 | -496.0 | -14.8125 | -15.0 |
72
+ | 0.1303 | 0.8377 | 800 | 0.8349 | -1.7734 | -1.7969 | 0.5195 | 0.0272 | -468.0 | -496.0 | -16.5 | -16.5 |
73
+ | 0.1614 | 0.9424 | 900 | 0.8078 | -2.2969 | -2.5 | 0.5332 | 0.1992 | -540.0 | -548.0 | -16.375 | -16.375 |
74
+ | 0.0199 | 1.0471 | 1000 | 0.8233 | -2.2656 | -2.3906 | 0.4863 | 0.1279 | -528.0 | -544.0 | -15.4375 | -15.875 |
75
+ | 0.0348 | 1.1518 | 1100 | 0.8452 | -2.0469 | -2.1562 | 0.5039 | 0.1187 | -504.0 | -524.0 | -17.0 | -17.125 |
76
+ | 0.0186 | 1.2565 | 1200 | 0.8788 | -2.9219 | -3.0312 | 0.5098 | 0.1074 | -592.0 | -612.0 | -14.75 | -15.0625 |
77
+ | 0.0277 | 1.3613 | 1300 | 0.8304 | -2.7969 | -2.8906 | 0.5137 | 0.0928 | -576.0 | -600.0 | -14.25 | -14.5 |
78
+ | 0.0212 | 1.4660 | 1400 | 0.8990 | -2.7969 | -2.9062 | 0.5 | 0.1099 | -580.0 | -600.0 | -14.25 | -14.4375 |
79
+ | 0.0333 | 1.5707 | 1500 | 0.9111 | -3.2031 | -3.2969 | 0.5215 | 0.0981 | -620.0 | -640.0 | -12.1875 | -12.625 |
80
+ | 0.0163 | 1.6754 | 1600 | 0.9215 | -3.2188 | -3.3281 | 0.4941 | 0.1104 | -620.0 | -640.0 | -11.0625 | -11.5 |
81
+ | 0.0309 | 1.7801 | 1700 | 0.9203 | -2.6719 | -2.7344 | 0.5059 | 0.0635 | -560.0 | -584.0 | -13.5625 | -13.8125 |
82
+ | 0.0228 | 1.8848 | 1800 | 0.9032 | -2.8594 | -2.9531 | 0.4941 | 0.0972 | -584.0 | -604.0 | -13.3125 | -13.5625 |
83
+ | 0.0116 | 1.9895 | 1900 | 0.9123 | -3.0156 | -3.125 | 0.5 | 0.1187 | -600.0 | -620.0 | -13.375 | -13.625 |
84
+ | 0.0011 | 2.0942 | 2000 | 0.9715 | -3.2656 | -3.4531 | 0.4980 | 0.1865 | -636.0 | -644.0 | -13.0625 | -13.3125 |
85
+ | 0.0019 | 2.1990 | 2100 | 1.0378 | -3.6719 | -3.9062 | 0.5098 | 0.2393 | -680.0 | -684.0 | -12.5 | -12.8125 |
86
+ | 0.0011 | 2.3037 | 2200 | 1.0456 | -3.7188 | -3.9375 | 0.5020 | 0.2227 | -684.0 | -692.0 | -12.8125 | -13.125 |
87
+ | 0.0009 | 2.4084 | 2300 | 1.0567 | -3.75 | -3.9688 | 0.5020 | 0.2217 | -684.0 | -692.0 | -12.9375 | -13.25 |
88
+ | 0.0022 | 2.5131 | 2400 | 1.0450 | -3.7188 | -3.9062 | 0.4961 | 0.1953 | -680.0 | -692.0 | -13.0 | -13.3125 |
89
+ | 0.0013 | 2.6178 | 2500 | 1.0499 | -3.7656 | -3.9688 | 0.5020 | 0.2080 | -684.0 | -696.0 | -12.9375 | -13.25 |
90
+ | 0.0006 | 2.7225 | 2600 | 1.0572 | -3.7812 | -3.9844 | 0.4961 | 0.2100 | -688.0 | -696.0 | -12.9375 | -13.25 |
91
+ | 0.0007 | 2.8272 | 2700 | 1.0600 | -3.7969 | -4.0 | 0.5020 | 0.2168 | -692.0 | -700.0 | -12.9375 | -13.25 |
92
+ | 0.0012 | 2.9319 | 2800 | 1.0609 | -3.7969 | -4.0 | 0.5 | 0.2148 | -692.0 | -700.0 | -12.9375 | -13.25 |
93
 
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  ### Framework versions
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