---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment_handbook-handbook
- generated_from_trainer
datasets:
- princeton-nlp/mistral-instruct-ultrafeedback
model-index:
- name: Mistral-7B-Base-SimPO2-5e-7
  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/tengxiao01/huggingface/runs/jcsdn1jt)
# Mistral-7B-Base-SimPO2-5e-7

This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the princeton-nlp/mistral-instruct-ultrafeedback dataset.
It achieves the following results on the evaluation set:
- Logits/chosen: -2.9000
- Logits/rejected: -2.8928
- Logps/chosen: -1.1346
- Logps/rejected: -1.2466
- Loss: -0.0708
- Rewards/accuracies: 0.5758
- Rewards/chosen: -1.1346
- Rewards/margins: 0.1120
- Rewards/rejected: -1.2466

## 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-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_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 |
|:-------------:|:------:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
| -0.0905       | 0.8573 | 400  | -2.9000       | -2.8928         | -1.1346      | -1.2466        | -0.0708         | 0.5758             | -1.1346        | 0.1120          | -1.2466          |


### Framework versions

- Transformers 4.42.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1