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---
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_completion_only_5_epochs
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_completion_only_5_epochs
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: 0.1658
## 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: 5.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.1419 | 0.3690 | 250 | 0.1250 |
| 0.1404 | 0.7380 | 500 | 0.1611 |
| 0.1554 | 1.1070 | 750 | 0.1358 |
| 0.1426 | 1.4760 | 1000 | 0.1543 |
| 0.1194 | 1.8450 | 1250 | 0.1823 |
| 0.0865 | 2.2140 | 1500 | 0.1511 |
| 0.0728 | 2.5830 | 1750 | 0.1463 |
| 0.4116 | 2.9520 | 2000 | 0.1224 |
| 0.0405 | 3.3210 | 2250 | 0.1939 |
| 0.0573 | 3.6900 | 2500 | 0.1324 |
| 0.0237 | 4.0590 | 2750 | 0.1657 |
| 0.0208 | 4.4280 | 3000 | 0.1818 |
| 0.0111 | 4.7970 | 3250 | 0.1658 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1 |