File size: 2,822 Bytes
0337d05 |
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-Coccur-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-Coccur-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-Coccur-q0_25_preference dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5440
- Rewards/chosen: -2.3911
- Rewards/rejected: -4.1460
- Rewards/accuracies: 0.7188
- Rewards/margins: 1.7550
- Logps/rejected: -201.5194
- Logps/chosen: -183.7933
- Logits/rejected: -2.7049
- Logits/chosen: -2.7311
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5904 | 0.6944 | 50 | 0.5585 | 0.1767 | -0.5308 | 0.6953 | 0.7075 | -165.3675 | -158.1156 | -2.7400 | -2.7505 |
| 0.2124 | 1.3889 | 100 | 0.5330 | -0.9785 | -2.2414 | 0.7344 | 1.2630 | -182.4733 | -169.6674 | -2.6846 | -2.7028 |
| 0.1027 | 2.0833 | 150 | 0.5209 | -1.3289 | -2.7382 | 0.7305 | 1.4093 | -187.4415 | -173.1719 | -2.7648 | -2.7841 |
| 0.0793 | 2.7778 | 200 | 0.5435 | -2.3758 | -4.1313 | 0.7227 | 1.7554 | -201.3717 | -183.6412 | -2.7055 | -2.7316 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
|