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---
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- ultrachat_200k/data
base_model: Mistral-7B-Instruct-v0.1
model-index:
- name: zephyr-7b-sft-qlora
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. -->
# zephyr-7b-sft-qlora
This model is a fine-tuned version of [Mistral-7B-Instruct-v0.1](https://huggingface.co//mntcephfs/data/med/guimingchen/models/general/Mistral-7B-Instruct-v0.1) on the /mntcephfs/lab_data/chennuo/MEAL/models/ultrachat_200k/data dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0257
## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- total_eval_batch_size: 8
- 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 | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.9852 | 1.0 | 33490 | 1.0257 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1 |