---
base_model: mistralai/Mistral-7B-v0.1
datasets:
- HuggingFaceH4/ultrafeedback_binarized
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
model-index:
- name: Mistral-7B-base-simpo-qlora
  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/nlp-xiaobo/huggingface/runs/fgjarr1f)
# Mistral-7B-base-simpo-qlora

This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-qlora](https://huggingface.co/alignment-handbook/zephyr-7b-sft-qlora) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5543
- Rewards/chosen: -2.0201
- Rewards/rejected: -2.5529
- Rewards/accuracies: 0.6215
- Rewards/margins: 0.5328
- Logps/rejected: -1.2765
- Logps/chosen: -1.0100
- Logits/rejected: -2.1352
- Logits/chosen: -2.2380

## 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: 3e-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|:-------------:|:------:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
| 1.6117        | 0.1047 | 400  | -2.2513       | -2.1455         | -0.9526      | -1.1212        | 1.6171          | 0.6010             | -1.9052        | 0.3373          | -2.2425          |
| 1.5829        | 0.2094 | 800  | -2.2393       | -2.1341         | -0.9938      | -1.2007        | 1.5888          | 0.6160             | -1.9876        | 0.4139          | -2.4015          |
| 1.5829        | 0.3141 | 1200 | -2.2356       | -2.1315         | -0.9915      | -1.2316        | 1.5656          | 0.6235             | -1.9830        | 0.4802          | -2.4632          |
| 1.6544        | 0.4187 | 1600 | -2.2392       | -2.1362         | -1.0204      | -1.2795        | 1.5601          | 0.6205             | -2.0408        | 0.5182          | -2.5590          |
| 1.4432        | 0.5234 | 2000 | -2.2398       | -2.1370         | -1.0143      | -1.2770        | 1.5560          | 0.6215             | -2.0287        | 0.5254          | -2.5541          |
| 1.5835        | 0.6281 | 2400 | -2.2387       | -2.1360         | -1.0393      | -1.3078        | 1.5582          | 0.6215             | -2.0787        | 0.5369          | -2.6156          |
| 1.5021        | 0.7328 | 2800 | -2.2395       | -2.1368         | -1.0048      | -1.2707        | 1.5540          | 0.6235             | -2.0096        | 0.5317          | -2.5414          |
| 1.6684        | 0.8375 | 3200 | -2.2405       | -2.1379         | -1.0095      | -1.2763        | 1.5542          | 0.6215             | -2.0191        | 0.5334          | -2.5525          |
| 1.5034        | 0.9422 | 3600 | -2.2372       | -2.1342         | -1.0110      | -1.2775        | 1.5546          | 0.6210             | -2.0219        | 0.5331          | -2.5550          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.42.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1