File size: 2,810 Bytes
70b58fb
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
library_name: transformers
license: other
base_model: llava-hf/llava-v1.6-mistral-7b-hf
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: RLAIF-V-L0-q0_25_preference
  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. -->

# RLAIF-V-L0-q0_25_preference

This model is a fine-tuned version of [llava-hf/llava-v1.6-mistral-7b-hf](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf) on the RLAIF-V-L0-q0_25_preference dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5525
- Rewards/chosen: -2.5933
- Rewards/rejected: -4.2536
- Rewards/accuracies: 0.7344
- Rewards/margins: 1.6603
- Logps/rejected: -203.2228
- Logps/chosen: -183.7414
- Logits/rejected: -2.2176
- Logits/chosen: -2.2545

## 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: 1e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5342        | 0.6944 | 50   | 0.5209          | -0.2071        | -0.9491          | 0.7148             | 0.7420          | -170.1774      | -159.8791    | -2.4678         | -2.4995       |
| 0.217         | 1.3889 | 100  | 0.5167          | -1.1670        | -2.3865          | 0.7070             | 1.2195          | -184.5513      | -169.4779    | -2.4044         | -2.4350       |
| 0.105         | 2.0833 | 150  | 0.5275          | -2.3365        | -3.9689          | 0.7383             | 1.6324          | -200.3754      | -181.1734    | -2.1635         | -2.2023       |
| 0.0911        | 2.7778 | 200  | 0.5503          | -2.5532        | -4.2135          | 0.7227             | 1.6603          | -202.8217      | -183.3405    | -2.2203         | -2.2570       |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3