---
license: apache-2.0
base_model: AmberYifan/mistral-safe-sft-full
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- AmberYifan/sft-spin-kcenter-5k
model-index:
- name: sft-spin-kcenter-5k
  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. -->

# sft-spin-kcenter-5k

This model is a fine-tuned version of [AmberYifan/mistral-safe-sft-full](https://huggingface.co/AmberYifan/mistral-safe-sft-full) on the AmberYifan/sft-spin-kcenter-5k dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9619
- Rewards/real: 0.2019
- Rewards/generated: -0.1441
- Rewards/accuracies: 0.8906
- Rewards/margins: 0.3460
- Logps/generated: -259.6614
- Logps/real: -210.6393
- Logits/generated: -2.6617
- Logits/real: -2.6095

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/real | Rewards/generated | Rewards/accuracies | Rewards/margins | Logps/generated | Logps/real | Logits/generated | Logits/real |
|:-------------:|:------:|:----:|:---------------:|:------------:|:-----------------:|:------------------:|:---------------:|:---------------:|:----------:|:----------------:|:-----------:|
| 0.0           | 0.6369 | 100  | 0.9619          | 0.2019       | -0.1441           | 0.8906             | 0.3460          | -259.6614       | -210.6393  | -2.6617          | -2.6095     |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.2.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1