---
license: other
base_model: Qwen/Qwen1.5-0.5B
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/deita-6k-v0-sft
model-index:
- name: qwen-1.5-0.5b-sft-v1.0
  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. -->

# qwen-1.5-0.5b-sft-v1.0

This model is a fine-tuned version of [Qwen/Qwen1.5-0.5B](https://huggingface.co/Qwen/Qwen1.5-0.5B) on the HuggingFaceH4/deita-6k-v0-sft dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2566

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.3015        | 1.0   | 237  | 1.2711          |
| 1.2352        | 2.0   | 474  | 1.2562          |
| 1.1719        | 3.0   | 711  | 1.2566          |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
