File size: 3,216 Bytes
92d61ac |
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 |
---
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_cosi_new_step10_0_80
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_cosi_new_step10_0_80
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_cosi_new_step10_0_80 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5448
- Rewards/chosen: 0.4294
- Rewards/rejected: -2.4664
- Rewards/accuracies: 0.7969
- Rewards/margins: 2.8958
- Logps/rejected: -238.7556
- Logps/chosen: -244.1195
- Logits/rejected: -2.2467
- Logits/chosen: -2.2820
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5529 | 0.4673 | 50 | 0.5947 | 0.8739 | -0.2594 | 0.7318 | 1.1333 | -216.6857 | -239.6745 | -2.0297 | -2.0593 |
| 0.5159 | 0.9346 | 100 | 0.5286 | -0.2159 | -2.0191 | 0.7812 | 1.8031 | -234.2824 | -250.5727 | -1.9168 | -1.9646 |
| 0.2666 | 1.4019 | 150 | 0.5667 | 0.7904 | -1.6811 | 0.7891 | 2.4715 | -230.9029 | -240.5096 | -2.2443 | -2.2847 |
| 0.3127 | 1.8692 | 200 | 0.5356 | 0.6480 | -1.8158 | 0.8047 | 2.4639 | -232.2502 | -241.9330 | -2.3879 | -2.4148 |
| 0.152 | 2.3364 | 250 | 0.5442 | 0.6088 | -2.0845 | 0.7891 | 2.6933 | -234.9365 | -242.3255 | -2.2443 | -2.2814 |
| 0.1431 | 2.8037 | 300 | 0.5450 | 0.4225 | -2.4743 | 0.7943 | 2.8968 | -238.8347 | -244.1887 | -2.2467 | -2.2822 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
|