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---
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
|