File size: 2,851 Bytes
4fc7839
 
 
 
 
 
 
7d94d4f
4fc7839
 
 
 
 
 
 
 
 
 
 
7d94d4f
4fc7839
7d94d4f
 
 
 
 
 
 
 
 
 
 
 
4fc7839
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7d94d4f
4fc7839
 
 
7d94d4f
 
 
 
4fc7839
 
 
 
 
 
 
7d94d4f
 
 
 
 
4fc7839
 
 
 
 
 
 
 
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
---
library_name: transformers
license: gemma
base_model: google/gemma-7b
tags:
- trl
- orpo
- alignment-handbook
- generated_from_trainer
model-index:
- name: gemma-7b-orpo-low-quality
  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. -->

# gemma-7b-orpo-low-quality

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co./google/gemma-7b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6395
- Rewards/chosen: -0.0601
- Rewards/rejected: -0.0755
- Rewards/accuracies: 0.6029
- Rewards/margins: 0.0153
- Logps/rejected: -1.5091
- Logps/chosen: -1.2026
- Logits/rejected: 275.9735
- Logits/chosen: 286.3763
- Nll Loss: 1.5847
- Log Odds Ratio: -0.6702
- Log Odds Chosen: 0.4438

## 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: 5e-06
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_steps: 100
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.4933        | 0.9976 | 157  | 1.4686          | -0.0501        | -0.0608          | 0.5776             | 0.0107          | -1.2166        | -1.0023      | 307.1602        | 318.2524      | 1.4127   | -0.6558        | 0.3240          |
| 1.036         | 1.9952 | 314  | 1.4194          | -0.0493        | -0.0612          | 0.5668             | 0.0118          | -1.2231        | -0.9867      | 302.5974        | 312.9305      | 1.3670   | -0.6609        | 0.3487          |
| 0.56          | 2.9929 | 471  | 1.6395          | -0.0601        | -0.0755          | 0.6029             | 0.0153          | -1.5091        | -1.2026      | 275.9735        | 286.3763      | 1.5847   | -0.6702        | 0.4438          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1