---
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-L2EXPO-25-8
  results: []
---

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[<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/1j4l9dwx)
# mistral-7b-expo-7b-L2EXPO-25-8

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: 0.4420
- Objective: 0.4416
- Reward Accuracy: 0.6655
- Logp Accuracy: 0.6499
- Log Diff Policy: 15.7908
- Chosen Logps: -168.1699
- Rejected Logps: -183.9607
- Chosen Rewards: -0.7349
- Rejected Rewards: -0.8890
- Logits: -2.0174

## 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  |
|:-------------:|:------:|:----:|:---------------:|:---------:|:---------------:|:-------------:|:---------------:|:------------:|:--------------:|:--------------:|:----------------:|:-------:|
| 0.6077        | 0.1517 | 100  | 0.5074          | 0.5043    | 0.5702          | 0.5254        | 0.9522          | -93.2911     | -94.2433       | 0.0139         | 0.0082           | -2.2027 |
| 0.5413        | 0.3033 | 200  | 0.4873          | 0.4899    | 0.6037          | 0.5937        | 8.2778          | -125.3062    | -133.5840      | -0.3062        | -0.3852          | -1.9290 |
| 0.5306        | 0.4550 | 300  | 0.4690          | 0.4694    | 0.6373          | 0.6267        | 12.8023         | -128.2087    | -141.0110      | -0.3353        | -0.4595          | -1.9229 |
| 0.4809        | 0.6067 | 400  | 0.4566          | 0.4556    | 0.6507          | 0.6390        | 13.4130         | -110.8082    | -124.2212      | -0.1613        | -0.2916          | -2.1010 |
| 0.5005        | 0.7583 | 500  | 0.4521          | 0.4527    | 0.6566          | 0.6538        | 16.5186         | -141.8083    | -158.3269      | -0.4713        | -0.6326          | -2.0970 |
| 0.4543        | 0.9100 | 600  | 0.4501          | 0.4510    | 0.6692          | 0.6586        | 17.7658         | -179.5024    | -197.2682      | -0.8482        | -1.0220          | -2.0605 |


### Framework versions

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