File size: 2,836 Bytes
5a0ce29 |
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: AA_preference_cocour_new_step10_0_60
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. -->
# AA_preference_cocour_new_step10_0_60
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 AA_preference_cocour_new_step10_0_60 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5132
- Rewards/chosen: 1.2483
- Rewards/rejected: -1.4384
- Rewards/accuracies: 0.8090
- Rewards/margins: 2.6868
- Logps/rejected: -217.5475
- Logps/chosen: -242.1045
- Logits/rejected: -2.5237
- Logits/chosen: -2.5348
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5367 | 0.6231 | 50 | 0.5755 | 1.1959 | -0.1615 | 0.7604 | 1.3575 | -204.7787 | -242.6288 | -2.3101 | -2.3204 |
| 0.2278 | 1.2461 | 100 | 0.5325 | 1.6096 | -0.6681 | 0.7986 | 2.2777 | -209.8443 | -238.4921 | -2.6060 | -2.6072 |
| 0.2926 | 1.8692 | 150 | 0.5151 | 1.0491 | -1.4143 | 0.8194 | 2.4633 | -217.3059 | -244.0971 | -2.4769 | -2.4878 |
| 0.1423 | 2.4922 | 200 | 0.5126 | 1.3148 | -1.3120 | 0.8125 | 2.6268 | -216.2832 | -241.4400 | -2.5411 | -2.5506 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
|