|
--- |
|
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_70 |
|
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_70 |
|
|
|
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_70 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5221 |
|
- Rewards/chosen: 0.8511 |
|
- Rewards/rejected: -1.7632 |
|
- Rewards/accuracies: 0.7827 |
|
- Rewards/margins: 2.6143 |
|
- Logps/rejected: -233.5941 |
|
- Logps/chosen: -246.8883 |
|
- Logits/rejected: -2.2402 |
|
- Logits/chosen: -2.2674 |
|
|
|
## 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 | |
|
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
|
| 0.5857 | 0.5348 | 50 | 0.5588 | 0.8626 | -0.4673 | 0.7202 | 1.3299 | -220.6345 | -246.7726 | -2.3950 | -2.4070 | |
|
| 0.2515 | 1.0695 | 100 | 0.5002 | 1.1633 | -0.7568 | 0.7827 | 1.9201 | -223.5298 | -243.7656 | -2.3802 | -2.3927 | |
|
| 0.2749 | 1.6043 | 150 | 0.5163 | 0.8806 | -1.4497 | 0.7738 | 2.3303 | -230.4583 | -246.5927 | -2.4269 | -2.4377 | |
|
| 0.148 | 2.1390 | 200 | 0.5244 | 1.0476 | -1.4591 | 0.7887 | 2.5067 | -230.5529 | -244.9229 | -2.2151 | -2.2425 | |
|
| 0.1437 | 2.6738 | 250 | 0.5224 | 0.8628 | -1.7441 | 0.7798 | 2.6069 | -233.4026 | -246.7709 | -2.2343 | -2.2617 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.45.2 |
|
- Pytorch 2.4.0+cu121 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.20.3 |
|
|
