---
language:
- zh
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- nycu-112-2-deeplearning-hw2
- generated_from_trainer
base_model: MediaTek-Research/Breeze-7B-Instruct-v1_0
datasets:
- DandinPower/ZH-Reading-Comprehension-Breeze-Instruct
model-index:
- name: breeze_7b_lora
  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. -->

# breeze_7b_lora

This model is a fine-tuned version of [MediaTek-Research/Breeze-7B-Instruct-v1_0](https://huggingface.co/MediaTek-Research/Breeze-7B-Instruct-v1_0) on the DandinPower/ZH-Reading-Comprehension-Breeze-Instruct dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9671

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 700
- num_epochs: 10.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.2919        | 0.3690 | 250  | 2.2932          |
| 2.2105        | 0.7380 | 500  | 2.1866          |
| 1.9287        | 1.1070 | 750  | 1.9796          |
| 1.8181        | 1.4760 | 1000 | 1.8416          |
| 1.6765        | 1.8450 | 1250 | 1.7156          |
| 1.4271        | 2.2140 | 1500 | 1.6054          |
| 1.3595        | 2.5830 | 1750 | 1.5071          |
| 1.2794        | 2.9520 | 2000 | 1.4263          |
| 1.0636        | 3.3210 | 2250 | 1.3707          |
| 1.0272        | 3.6900 | 2500 | 1.3044          |
| 0.8977        | 4.0590 | 2750 | 1.2597          |
| 0.8923        | 4.4280 | 3000 | 1.2184          |
| 0.8628        | 4.7970 | 3250 | 1.1737          |
| 0.6994        | 5.1661 | 3500 | 1.1514          |
| 0.7201        | 5.5351 | 3750 | 1.1209          |
| 0.7237        | 5.9041 | 4000 | 1.0931          |
| 0.6468        | 6.2731 | 4250 | 1.0740          |
| 0.6052        | 6.6421 | 4500 | 1.0472          |
| 0.5737        | 7.0111 | 4750 | 1.0360          |
| 0.5419        | 7.3801 | 5000 | 1.0246          |
| 0.5539        | 7.7491 | 5250 | 1.0027          |
| 0.4615        | 8.1181 | 5500 | 0.9947          |
| 0.4782        | 8.4871 | 5750 | 0.9851          |
| 0.4809        | 8.8561 | 6000 | 0.9699          |
| 0.4284        | 9.2251 | 6250 | 0.9738          |
| 0.4332        | 9.5941 | 6500 | 0.9696          |
| 0.4341        | 9.9631 | 6750 | 0.9671          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1