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OpenELM-1_1B-DPO-full-max-14-reward

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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_22-45-30_xe8545-a100-15/events.out.tfevents.1728260823.xe8545-a100-15.1088924.1 +3 -0
  6. runs/Oct07_13-55-26_xe8545-a100-15/events.out.tfevents.1728303084.xe8545-a100-15.1103626.0 +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: 1.1518
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- - Rewards/chosen: -4.0625
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- - Rewards/rejected: -4.5312
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- - Rewards/accuracies: 0.4980
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- - Rewards/margins: 0.4824
25
- - Logps/rejected: -744.0
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- - Logps/chosen: -724.0
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- - Logits/rejected: -15.25
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- - Logits/chosen: -15.5625
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
- | 0.05 | 0.1047 | 100 | 0.8594 | -2.0469 | -2.3906 | 0.5488 | 0.3496 | -528.0 | -524.0 | -9.3125 | -9.5625 |
66
- | 0.0695 | 0.2094 | 200 | 0.7369 | -1.2031 | -1.3984 | 0.4883 | 0.1953 | -428.0 | -438.0 | -12.9375 | -13.3125 |
67
- | 0.0402 | 0.3141 | 300 | 1.4284 | -4.5938 | -5.0 | 0.5195 | 0.4297 | -792.0 | -776.0 | -9.125 | -9.75 |
68
- | 0.0373 | 0.4188 | 400 | 0.8732 | -2.3906 | -2.5156 | 0.4902 | 0.1279 | -540.0 | -556.0 | -13.375 | -13.5625 |
69
- | 0.0289 | 0.5236 | 500 | 0.9761 | -3.5938 | -3.8906 | 0.4902 | 0.2871 | -676.0 | -680.0 | -15.0 | -15.25 |
70
- | 0.0549 | 0.6283 | 600 | 0.9004 | -2.3594 | -2.6094 | 0.4805 | 0.2539 | -548.0 | -556.0 | -15.0625 | -15.1875 |
71
- | 0.0385 | 0.7330 | 700 | 0.9997 | -3.125 | -3.25 | 0.4746 | 0.1299 | -612.0 | -632.0 | -11.5 | -11.875 |
72
- | 0.0303 | 0.8377 | 800 | 1.0037 | -2.7656 | -2.9375 | 0.4785 | 0.1748 | -584.0 | -596.0 | -13.75 | -14.0625 |
73
- | 0.0147 | 0.9424 | 900 | 1.1243 | -3.6094 | -3.7656 | 0.4824 | 0.1553 | -664.0 | -680.0 | -13.8125 | -14.1875 |
74
- | 0.0038 | 1.0471 | 1000 | 1.0635 | -3.5781 | -3.7969 | 0.4941 | 0.2158 | -668.0 | -676.0 | -13.8125 | -14.125 |
75
- | 0.0192 | 1.1518 | 1100 | 1.2317 | -4.1875 | -4.5625 | 0.4941 | 0.3711 | -744.0 | -736.0 | -14.0 | -14.25 |
76
- | 0.0035 | 1.2565 | 1200 | 1.1275 | -3.8125 | -4.0938 | 0.5195 | 0.2676 | -696.0 | -700.0 | -13.6875 | -14.0625 |
77
- | 0.0014 | 1.3613 | 1300 | 1.1072 | -3.8281 | -4.1875 | 0.5039 | 0.3672 | -708.0 | -700.0 | -10.3125 | -11.0 |
78
- | 0.0009 | 1.4660 | 1400 | 1.2158 | -4.1562 | -4.5938 | 0.5039 | 0.4570 | -748.0 | -732.0 | -15.6875 | -16.0 |
79
- | 0.0047 | 1.5707 | 1500 | 0.9804 | -3.4062 | -3.7656 | 0.5 | 0.3672 | -664.0 | -660.0 | -14.625 | -15.0625 |
80
- | 0.0009 | 1.6754 | 1600 | 1.0340 | -4.0312 | -4.4688 | 0.5137 | 0.4219 | -736.0 | -724.0 | -10.6875 | -11.4375 |
81
- | 0.0053 | 1.7801 | 1700 | 0.9808 | -3.4531 | -3.8125 | 0.5215 | 0.3730 | -672.0 | -664.0 | -16.125 | -16.25 |
82
- | 0.0006 | 1.8848 | 1800 | 0.9781 | -3.2812 | -3.5312 | 0.5098 | 0.2578 | -640.0 | -644.0 | -16.125 | -16.25 |
83
- | 0.0086 | 1.9895 | 1900 | 1.1759 | -4.1562 | -4.6562 | 0.5020 | 0.5195 | -756.0 | -732.0 | -15.4375 | -15.6875 |
84
- | 0.0001 | 2.0942 | 2000 | 1.1181 | -3.8594 | -4.3125 | 0.5 | 0.4473 | -720.0 | -704.0 | -15.4375 | -15.6875 |
85
- | 0.0145 | 2.1990 | 2100 | 1.1573 | -4.0312 | -4.5312 | 0.4980 | 0.4941 | -740.0 | -720.0 | -15.625 | -15.875 |
86
- | 0.0002 | 2.3037 | 2200 | 1.1923 | -4.2188 | -4.7188 | 0.4961 | 0.5234 | -760.0 | -740.0 | -15.0625 | -15.4375 |
87
- | 0.0005 | 2.4084 | 2300 | 1.1497 | -4.0 | -4.5 | 0.4902 | 0.4824 | -736.0 | -720.0 | -15.3125 | -15.5625 |
88
- | 0.0002 | 2.5131 | 2400 | 1.1575 | -4.0312 | -4.5312 | 0.4961 | 0.4902 | -740.0 | -720.0 | -15.375 | -15.6875 |
89
- | 0.0001 | 2.6178 | 2500 | 1.1676 | -4.0938 | -4.5938 | 0.4922 | 0.5039 | -748.0 | -728.0 | -15.25 | -15.5625 |
90
- | 0.0014 | 2.7225 | 2600 | 1.1490 | -4.0312 | -4.5 | 0.5020 | 0.4785 | -740.0 | -720.0 | -15.3125 | -15.625 |
91
- | 0.0002 | 2.8272 | 2700 | 1.1505 | -4.0312 | -4.5312 | 0.4961 | 0.4824 | -740.0 | -720.0 | -15.25 | -15.5625 |
92
- | 0.0002 | 2.9319 | 2800 | 1.1518 | -4.0625 | -4.5312 | 0.4980 | 0.4824 | -744.0 | -724.0 | -15.25 | -15.5625 |
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: 1.1668
21
+ - Rewards/chosen: -3.5938
22
+ - Rewards/rejected: -4.0
23
+ - Rewards/accuracies: 0.4902
24
+ - Rewards/margins: 0.4121
25
+ - Logps/rejected: -688.0
26
+ - Logps/chosen: -676.0
27
+ - Logits/rejected: -16.375
28
+ - Logits/chosen: -16.875
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
+ | 0.0562 | 0.1047 | 100 | 0.6971 | -1.2578 | -1.5703 | 0.5762 | 0.3145 | -446.0 | -444.0 | -9.3125 | -9.5625 |
66
+ | 0.0394 | 0.2094 | 200 | 0.7479 | -0.8516 | -1.0078 | 0.5195 | 0.1572 | -390.0 | -404.0 | -12.3125 | -12.75 |
67
+ | 0.0487 | 0.3141 | 300 | 0.9195 | -1.9922 | -2.3125 | 0.5176 | 0.3203 | -520.0 | -516.0 | -13.4375 | -13.6875 |
68
+ | 0.0454 | 0.4188 | 400 | 0.8309 | -1.4453 | -1.6016 | 0.4961 | 0.1543 | -448.0 | -462.0 | -15.625 | -15.75 |
69
+ | 0.0297 | 0.5236 | 500 | 0.8326 | -3.1094 | -3.375 | 0.5039 | 0.2734 | -628.0 | -628.0 | -15.5 | -15.6875 |
70
+ | 0.0434 | 0.6283 | 600 | 0.8373 | -1.6953 | -1.875 | 0.4941 | 0.1826 | -476.0 | -488.0 | -15.0 | -15.25 |
71
+ | 0.0496 | 0.7330 | 700 | 0.9407 | -3.7344 | -3.9688 | 0.5332 | 0.2236 | -684.0 | -692.0 | -9.5625 | -10.3125 |
72
+ | 0.0289 | 0.8377 | 800 | 1.0108 | -3.1406 | -3.25 | 0.4707 | 0.0991 | -612.0 | -632.0 | -13.0625 | -13.3125 |
73
+ | 0.0259 | 0.9424 | 900 | 1.0869 | -3.6094 | -3.7812 | 0.4648 | 0.1631 | -668.0 | -680.0 | -15.625 | -15.875 |
74
+ | 0.005 | 1.0471 | 1000 | 1.0944 | -3.4375 | -3.625 | 0.4570 | 0.1758 | -652.0 | -664.0 | -15.0625 | -15.25 |
75
+ | 0.0156 | 1.1518 | 1100 | 1.2452 | -4.4062 | -4.5938 | 0.4629 | 0.1973 | -748.0 | -760.0 | -16.5 | -16.625 |
76
+ | 0.0018 | 1.2565 | 1200 | 1.0496 | -3.7344 | -3.9219 | 0.4844 | 0.1885 | -680.0 | -692.0 | -15.5625 | -15.875 |
77
+ | 0.0046 | 1.3613 | 1300 | 1.0484 | -3.375 | -3.6094 | 0.4980 | 0.2402 | -648.0 | -656.0 | -14.9375 | -15.25 |
78
+ | 0.0041 | 1.4660 | 1400 | 0.9980 | -3.5156 | -3.8438 | 0.5137 | 0.3379 | -676.0 | -668.0 | -13.8125 | -14.3125 |
79
+ | 0.0077 | 1.5707 | 1500 | 1.0434 | -3.1719 | -3.5156 | 0.4902 | 0.3535 | -640.0 | -636.0 | -13.875 | -14.375 |
80
+ | 0.0016 | 1.6754 | 1600 | 1.0882 | -3.8594 | -4.2812 | 0.4922 | 0.4141 | -716.0 | -704.0 | -12.4375 | -12.9375 |
81
+ | 0.0042 | 1.7801 | 1700 | 1.0261 | -3.3438 | -3.7656 | 0.4941 | 0.4238 | -664.0 | -652.0 | -15.5 | -15.9375 |
82
+ | 0.0005 | 1.8848 | 1800 | 1.0536 | -3.2344 | -3.5938 | 0.4961 | 0.3555 | -648.0 | -644.0 | -16.625 | -17.0 |
83
+ | 0.0083 | 1.9895 | 1900 | 1.1039 | -3.4844 | -3.8125 | 0.4883 | 0.3242 | -672.0 | -668.0 | -16.25 | -16.625 |
84
+ | 0.0003 | 2.0942 | 2000 | 1.1159 | -3.5156 | -3.8438 | 0.4922 | 0.3301 | -672.0 | -672.0 | -16.125 | -16.625 |
85
+ | 0.0027 | 2.1990 | 2100 | 1.1535 | -3.5938 | -4.0 | 0.4980 | 0.4043 | -688.0 | -680.0 | -16.125 | -16.625 |
86
+ | 0.0003 | 2.3037 | 2200 | 1.1505 | -3.5781 | -3.9844 | 0.4902 | 0.4062 | -688.0 | -676.0 | -16.25 | -16.625 |
87
+ | 0.0006 | 2.4084 | 2300 | 1.1535 | -3.5469 | -3.9531 | 0.4902 | 0.4023 | -684.0 | -672.0 | -16.25 | -16.75 |
88
+ | 0.0002 | 2.5131 | 2400 | 1.1581 | -3.5781 | -3.9844 | 0.4922 | 0.4082 | -688.0 | -676.0 | -16.25 | -16.625 |
89
+ | 0.0001 | 2.6178 | 2500 | 1.1609 | -3.5625 | -3.9688 | 0.4961 | 0.4082 | -684.0 | -672.0 | -16.375 | -16.75 |
90
+ | 0.0008 | 2.7225 | 2600 | 1.1668 | -3.5938 | -4.0 | 0.4922 | 0.4121 | -688.0 | -676.0 | -16.375 | -16.75 |
91
+ | 0.0002 | 2.8272 | 2700 | 1.1668 | -3.5938 | -4.0 | 0.4902 | 0.4121 | -688.0 | -676.0 | -16.375 | -16.75 |
92
+ | 0.0003 | 2.9319 | 2800 | 1.1668 | -3.5938 | -4.0 | 0.4902 | 0.4121 | -688.0 | -676.0 | -16.375 | -16.875 |
93
 
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  ### Framework versions
all_results.json CHANGED
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