---
base_model: hZzy/mistral-7b-sft-25-1
datasets:
- hZzy/direction_right2
library_name: peft
license: apache-2.0
tags:
- alignment-handbook
- ndcg
- trl
- expo
- generated_from_trainer
model-index:
- name: mistral-7b-expo-7b-IPO-25-2
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/zhiyuzha-university-of-florida/huggingface/runs/cw0lh48k)
# mistral-7b-expo-7b-IPO-25-2

This model is a fine-tuned version of [hZzy/mistral-7b-sft-25-1](https://huggingface.co/hZzy/mistral-7b-sft-25-1) on the hZzy/direction_right2 dataset.
It achieves the following results on the evaluation set:
- Loss: 8.3755
- Objective: 8.4853
- Reward Accuracy: 0.6261
- Logp Accuracy: 0.5450
- Log Diff Policy: 2.3621
- Chosen Logps: -94.1866
- Rejected Logps: -96.5486
- Chosen Rewards: 0.0248
- Rejected Rewards: -0.0742
- Logits: -2.1694

## 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: 5e-06
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 12
- total_train_batch_size: 108
- total_eval_batch_size: 9
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Objective | Reward Accuracy | Logp Accuracy | Log Diff Policy | Chosen Logps | Rejected Logps | Chosen Rewards | Rejected Rewards | Logits  |
|:-------------:|:------:|:----:|:---------------:|:---------:|:---------------:|:-------------:|:---------------:|:------------:|:--------------:|:--------------:|:----------------:|:-------:|
| 9.358         | 0.1517 | 100  | 9.4767          | 9.4748    | 0.5584          | 0.5282        | 0.9202          | -92.3263     | -93.2465       | 0.1178         | 0.0909           | -2.1941 |
| 8.4865        | 0.3033 | 200  | 8.7651          | 8.8251    | 0.6121          | 0.5436        | 1.7419          | -92.0866     | -93.8284       | 0.1298         | 0.0618           | -2.2153 |
| 8.2077        | 0.4550 | 300  | 8.5507          | 8.6214    | 0.6264          | 0.5461        | 2.2164          | -92.5313     | -94.7477       | 0.1076         | 0.0158           | -2.2241 |
| 7.7431        | 0.6067 | 400  | 8.4722          | 8.5772    | 0.6314          | 0.5503        | 2.3954          | -90.6295     | -93.0249       | 0.2026         | 0.1020           | -2.2473 |
| 7.822         | 0.7583 | 500  | 8.4631          | 8.5834    | 0.6284          | 0.5445        | 2.3357          | -89.8860     | -92.2217       | 0.2398         | 0.1421           | -2.2090 |
| 7.6491        | 0.9100 | 600  | 8.4053          | 8.5433    | 0.6295          | 0.5445        | 2.2425          | -91.4902     | -93.7327       | 0.1596         | 0.0666           | -2.2060 |


### Framework versions

- PEFT 0.11.1
- Transformers 4.42.0
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.19.1