File size: 5,827 Bytes
4db68ba
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
---
license: apache-2.0
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: TheBloke/OpenHermes-2-Mistral-7B-GPTQ
model-index:
- name: openhermes-mistral-dpo-gptq
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# openhermes-mistral-dpo-gptq

This model is a fine-tuned version of [TheBloke/OpenHermes-2-Mistral-7B-GPTQ](https://huggingface.co/TheBloke/OpenHermes-2-Mistral-7B-GPTQ) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4346
- Rewards/chosen: 0.6886
- Rewards/rejected: -0.1517
- Rewards/accuracies: 0.875
- Rewards/margins: 0.8403
- Logps/rejected: -258.0681
- Logps/chosen: -269.4644
- Logits/rejected: -2.3873
- Logits/chosen: -2.4450

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6927        | 0.02  | 5    | 0.6723          | -0.0624        | -0.1130          | 0.5                | 0.0506          | -257.6814      | -276.9746    | -2.3921         | -2.4532       |
| 0.6896        | 0.04  | 10   | 0.6814          | -0.0837        | -0.1949          | 0.5625             | 0.1113          | -258.5006      | -277.1875    | -2.3785         | -2.4393       |
| 0.7286        | 0.06  | 15   | 0.7217          | -0.1116        | -0.2049          | 0.8125             | 0.0933          | -258.6005      | -277.4668    | -2.3732         | -2.4343       |
| 0.6049        | 0.08  | 20   | 0.6488          | -0.5231        | -0.7234          | 0.9375             | 0.2003          | -263.7849      | -281.5815    | -2.3599         | -2.4201       |
| 3.1019        | 0.1   | 25   | 0.6202          | -0.7269        | -1.0069          | 0.9375             | 0.2800          | -266.6205      | -283.6199    | -2.3529         | -2.4132       |
| 3.4522        | 0.12  | 30   | 0.6238          | -0.8793        | -1.2160          | 0.875              | 0.3367          | -268.7114      | -285.1440    | -2.3418         | -2.4001       |
| 1.7538        | 0.14  | 35   | 0.6336          | -0.5977        | -0.8794          | 0.875              | 0.2816          | -265.3451      | -282.3282    | -2.3479         | -2.4068       |
| 0.6167        | 0.16  | 40   | 0.6979          | 0.0308         | -0.1700          | 0.8125             | 0.2008          | -258.2513      | -276.0429    | -2.3591         | -2.4196       |
| 1.5103        | 0.18  | 45   | 0.7053          | 0.0521         | -0.1713          | 0.875              | 0.2233          | -258.2638      | -275.8300    | -2.3607         | -2.4207       |
| 0.6762        | 0.2   | 50   | 0.7144          | 0.1606         | -0.1470          | 0.875              | 0.3076          | -258.0209      | -274.7448    | -2.3658         | -2.4243       |
| 0.6587        | 0.22  | 55   | 0.7123          | 0.1399         | -0.2934          | 0.8125             | 0.4333          | -259.4854      | -274.9521    | -2.3670         | -2.4244       |
| 0.7563        | 0.24  | 60   | 0.7987          | 0.4547         | 0.0155           | 0.8125             | 0.4391          | -256.3959      | -271.8042    | -2.3793         | -2.4378       |
| 0.8208        | 0.26  | 65   | 0.8288          | 1.0234         | 0.5622           | 0.8125             | 0.4611          | -250.9289      | -266.1172    | -2.4012         | -2.4618       |
| 0.9904        | 0.28  | 70   | 0.7683          | 1.4763         | 0.9615           | 0.8125             | 0.5148          | -246.9362      | -261.5881    | -2.4184         | -2.4798       |
| 0.8327        | 0.3   | 75   | 0.6556          | 1.6107         | 1.0087           | 0.8125             | 0.6019          | -246.4639      | -260.2441    | -2.4218         | -2.4838       |
| 0.8238        | 0.32  | 80   | 0.5524          | 1.5571         | 0.8762           | 0.8125             | 0.6809          | -247.7892      | -260.7801    | -2.4168         | -2.4797       |
| 0.7712        | 0.34  | 85   | 0.5144          | 1.3444         | 0.6352           | 0.8125             | 0.7092          | -250.1996      | -262.9072    | -2.4079         | -2.4697       |
| 0.691         | 0.36  | 90   | 0.4688          | 1.0225         | 0.2544           | 0.875              | 0.7682          | -254.0075      | -266.1254    | -2.3981         | -2.4588       |
| 0.6386        | 0.38  | 95   | 0.4490          | 0.8498         | 0.0425           | 0.875              | 0.8074          | -256.1265      | -267.8524    | -2.3927         | -2.4521       |
| 0.6413        | 0.4   | 100  | 0.4346          | 0.6886         | -0.1517          | 0.875              | 0.8403          | -258.0681      | -269.4644    | -2.3873         | -2.4450       |


### Framework versions

- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.17.1
- Tokenizers 0.15.2