LBK95 commited on
Commit
c6e580e
·
verified ·
1 Parent(s): 03aef6c

End of training

Browse files
Files changed (1) hide show
  1. README.md +80 -0
README.md ADDED
@@ -0,0 +1,80 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: meta-llama/Llama-2-7b-hf
3
+ library_name: peft
4
+ license: llama2
5
+ tags:
6
+ - trl
7
+ - dpo
8
+ - generated_from_trainer
9
+ model-index:
10
+ - name: Llama-2-7b-hf-DPO-LookAhead-5_TTree1.4_TT0.9_TP0.7_TE0.2_V4
11
+ results: []
12
+ ---
13
+
14
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
15
+ should probably proofread and complete it, then remove this comment. -->
16
+
17
+ # Llama-2-7b-hf-DPO-LookAhead-5_TTree1.4_TT0.9_TP0.7_TE0.2_V4
18
+
19
+ This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the None dataset.
20
+ It achieves the following results on the evaluation set:
21
+ - Loss: 1.2125
22
+ - Rewards/chosen: -3.3104
23
+ - Rewards/rejected: -2.9319
24
+ - Rewards/accuracies: 0.4167
25
+ - Rewards/margins: -0.3786
26
+ - Logps/rejected: -192.9225
27
+ - Logps/chosen: -170.2794
28
+ - Logits/rejected: 0.1199
29
+ - Logits/chosen: 0.1595
30
+
31
+ ## Model description
32
+
33
+ More information needed
34
+
35
+ ## Intended uses & limitations
36
+
37
+ More information needed
38
+
39
+ ## Training and evaluation data
40
+
41
+ More information needed
42
+
43
+ ## Training procedure
44
+
45
+ ### Training hyperparameters
46
+
47
+ The following hyperparameters were used during training:
48
+ - learning_rate: 5e-05
49
+ - train_batch_size: 2
50
+ - eval_batch_size: 2
51
+ - seed: 42
52
+ - gradient_accumulation_steps: 2
53
+ - total_train_batch_size: 4
54
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
55
+ - lr_scheduler_type: cosine
56
+ - lr_scheduler_warmup_steps: 10
57
+ - num_epochs: 3
58
+
59
+ ### Training results
60
+
61
+ | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
62
+ |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
63
+ | 0.6179 | 0.3027 | 79 | 0.7115 | -0.1031 | -0.0593 | 0.25 | -0.0438 | -164.1966 | -138.2057 | 0.5429 | 0.5748 |
64
+ | 0.6065 | 0.6054 | 158 | 0.7348 | -0.0751 | 0.0129 | 0.25 | -0.0879 | -163.4753 | -137.9259 | 0.5242 | 0.5565 |
65
+ | 0.621 | 0.9080 | 237 | 0.7932 | -0.0433 | 0.1366 | 0.5 | -0.1800 | -162.2375 | -137.6083 | 0.4932 | 0.5259 |
66
+ | 0.4714 | 1.2107 | 316 | 0.7928 | -0.6963 | -0.5927 | 0.5 | -0.1037 | -169.5308 | -144.1387 | 0.4698 | 0.5037 |
67
+ | 0.3829 | 1.5134 | 395 | 0.8637 | -1.6604 | -1.5528 | 0.3333 | -0.1075 | -179.1323 | -153.7787 | 0.3664 | 0.4026 |
68
+ | 0.3589 | 1.8161 | 474 | 0.9222 | -1.4397 | -1.1360 | 0.25 | -0.3037 | -174.9637 | -151.5720 | 0.3400 | 0.3770 |
69
+ | 0.2138 | 2.1188 | 553 | 0.9860 | -1.9991 | -1.6486 | 0.3333 | -0.3505 | -180.0903 | -157.1666 | 0.2605 | 0.2992 |
70
+ | 0.0437 | 2.4215 | 632 | 1.1781 | -3.1628 | -2.7961 | 0.4167 | -0.3666 | -191.5652 | -168.8030 | 0.1441 | 0.1838 |
71
+ | 0.1667 | 2.7241 | 711 | 1.2125 | -3.3104 | -2.9319 | 0.4167 | -0.3786 | -192.9225 | -170.2794 | 0.1199 | 0.1595 |
72
+
73
+
74
+ ### Framework versions
75
+
76
+ - PEFT 0.12.0
77
+ - Transformers 4.44.0
78
+ - Pytorch 2.4.0+cu121
79
+ - Datasets 3.1.0
80
+ - Tokenizers 0.19.1