Hugging Face's logo

tyzhu
/
lmind_nq_train6000_eval6489_v1_reciteonly_qa_v3_lora2

PEFT
Safetensors
Generated from Trainer
Eval Results
Model card Files Community
tyzhu commited on
Commit
854c0ed
•
1 Parent(s): 6b08832

Model save

Browse files
Files changed (1) hide show
  1. README.md +22 -22
README.md CHANGED
@@ -15,8 +15,8 @@ should probably proofread and complete it, then remove this comment. -->
15
 
16
  This model was trained from scratch on an unknown dataset.
17
  It achieves the following results on the evaluation set:
18
- - Loss: 2.3138
19
- - Accuracy: 0.6569
20
 
21
  ## Model description
22
 
@@ -53,26 +53,26 @@ The following hyperparameters were used during training:
53
 
54
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
55
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
56
- | 1.0895 | 1.0 | 187 | 1.0317 | 0.6904 |
57
- | 0.9959 | 2.0 | 375 | 1.0319 | 0.6908 |
58
- | 0.9099 | 3.0 | 562 | 1.0512 | 0.6890 |
59
- | 0.7893 | 4.0 | 750 | 1.0986 | 0.6843 |
60
- | 0.674 | 5.0 | 937 | 1.1695 | 0.6794 |
61
- | 0.5518 | 6.0 | 1125 | 1.2677 | 0.6744 |
62
- | 0.4364 | 7.0 | 1312 | 1.3770 | 0.6708 |
63
- | 0.3384 | 8.0 | 1500 | 1.4781 | 0.6685 |
64
- | 0.2488 | 9.0 | 1687 | 1.6224 | 0.6652 |
65
- | 0.1889 | 10.0 | 1875 | 1.7546 | 0.6625 |
66
- | 0.1469 | 11.0 | 2062 | 1.8724 | 0.6613 |
67
- | 0.12 | 12.0 | 2250 | 1.9857 | 0.6595 |
68
- | 0.1016 | 13.0 | 2437 | 2.0585 | 0.6597 |
69
- | 0.0917 | 14.0 | 2625 | 2.1262 | 0.6584 |
70
- | 0.0867 | 15.0 | 2812 | 2.1983 | 0.6578 |
71
- | 0.0832 | 16.0 | 3000 | 2.2629 | 0.6573 |
72
- | 0.0765 | 17.0 | 3187 | 2.2393 | 0.6581 |
73
- | 0.0762 | 18.0 | 3375 | 2.2691 | 0.6576 |
74
- | 0.0761 | 19.0 | 3562 | 2.2851 | 0.6581 |
75
- | 0.0754 | 19.95 | 3740 | 2.3138 | 0.6569 |
76
 
77
 
78
  ### Framework versions
 
15
 
16
  This model was trained from scratch on an unknown dataset.
17
  It achieves the following results on the evaluation set:
18
+ - Loss: 2.4922
19
+ - Accuracy: 0.6471
20
 
21
  ## Model description
22
 
 
53
 
54
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
55
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
56
+ | 1.2282 | 1.0 | 187 | 1.1749 | 0.6707 |
57
+ | 1.1429 | 2.0 | 375 | 1.1714 | 0.6710 |
58
+ | 1.0415 | 3.0 | 562 | 1.1815 | 0.6707 |
59
+ | 0.9188 | 4.0 | 750 | 1.2171 | 0.6683 |
60
+ | 0.8039 | 5.0 | 937 | 1.2718 | 0.6662 |
61
+ | 0.6782 | 6.0 | 1125 | 1.3539 | 0.6622 |
62
+ | 0.5567 | 7.0 | 1312 | 1.4447 | 0.6598 |
63
+ | 0.4472 | 8.0 | 1500 | 1.5391 | 0.6570 |
64
+ | 0.341 | 9.0 | 1687 | 1.6785 | 0.6536 |
65
+ | 0.2626 | 10.0 | 1875 | 1.8042 | 0.6515 |
66
+ | 0.2015 | 11.0 | 2062 | 1.9496 | 0.6488 |
67
+ | 0.1589 | 12.0 | 2250 | 2.0568 | 0.6477 |
68
+ | 0.1274 | 13.0 | 2437 | 2.1358 | 0.6477 |
69
+ | 0.1074 | 14.0 | 2625 | 2.2125 | 0.6475 |
70
+ | 0.097 | 15.0 | 2812 | 2.3376 | 0.6469 |
71
+ | 0.0901 | 16.0 | 3000 | 2.3907 | 0.6466 |
72
+ | 0.0816 | 17.0 | 3187 | 2.4377 | 0.6460 |
73
+ | 0.0796 | 18.0 | 3375 | 2.4466 | 0.6461 |
74
+ | 0.0786 | 19.0 | 3562 | 2.4673 | 0.6454 |
75
+ | 0.0784 | 19.95 | 3740 | 2.4922 | 0.6471 |
76
 
77
 
78
  ### Framework versions