Training procedure
Framework versions
- SWIFT 1.5.3
Base model information
- BaseModel Class QWenLMHeadModel
情感分类，输⼊⼀段⽂本, 模型可以给出对应的情感分类
环境准备
git clone https://github.com/modelscope/swift.git
cd swift
pip install -e .[llm]
代码
import os
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
import torch
from swift.llm import (
DatasetName, InferArguments, ModelType, SftArguments,
infer_main, sft_main, app_ui_main, merge_lora_main
)
model_type = ModelType.qwen_1_8b
sft_args = SftArguments(
model_type=model_type,
sft_type='lora',
train_dataset_sample=2000,
dataset=[DatasetName.jd_sentiment_zh],
output_dir='output')
result = sft_main(sft_args)
# adapter的⼤⼩: 6.1MiB
best_model_checkpoint = result['best_model_checkpoint']
print(f'best_model_checkpoint: {best_model_checkpoint}')
torch.cuda.empty_cache()
infer_args = InferArguments(
ckpt_dir=best_model_checkpoint,
load_dataset_config=True,
do_sample=False)
result = infer_main(infer_args)
结果展示
[PROMPT]Task: Sentiment Classification
Sentence: 店家太不负责任了，衣服质量太差劲了，和图片上的不一样
Category: negative, positive
Output: [OUTPUT]negative<|endoftext|>
[LABELS]negative
--------------------------------------------------
[PROMPT]Task: Sentiment Classification
Sentence: 送国际友人挺好的，不错不错！
Category: negative, positive
Output: [OUTPUT]positive<|endoftext|>
[LABELS]positive
--------------------------------------------------
[PROMPT]Task: Sentiment Classification
Sentence: 很好,装好一定很漂亮
Category: negative, positive
Output: [OUTPUT]positive<|endoftext|>
[LABELS]positive
--------------------------------------------------
[PROMPT]Task: Sentiment Classification
Sentence: 东西给你退回去了，你要黑我钱！！！
Category: negative, positive
Output: [OUTPUT]negative<|endoftext|>
[LABELS]negative
--------------------------------------------------
[PROMPT]Task: Sentiment Classification
Sentence: 送货很快，书是正品，买书一直京东是首选！
Category: negative, positive
Output: [OUTPUT]positive<|endoftext|>
[LABELS]positive
--------------------------------------------------
[PROMPT]Task: Sentiment Classification
Sentence: 口感相当的好 都想买第二次了
Category: negative, positive
Output: [OUTPUT]positive<|endoftext|>
[LABELS]positive
--------------------------------------------------
[PROMPT]Task: Sentiment Classification
Sentence: 硅胶味道太重，样子与图片差距太大
Category: negative, positive
Output: [OUTPUT]negative<|endoftext|>
[LABELS]negative
--------------------------------------------------
[PROMPT]Task: Sentiment Classification
Sentence: 很伤心，买了放到三星n4尽然不能用，客服各种推
Category: negative, positive
Output: [OUTPUT]negative<|endoftext|>
[LABELS]negative
--------------------------------------------------
[PROMPT]Task: Sentiment Classification
Sentence: 质量不错，大小合适，应当是正品！但是我买的是黑灰，发来的却是纯黑，懒得换了，给个差评，希望以后改进！
Category: negative, positive
Output: [OUTPUT]positive<|endoftext|>
[INFO:swift] save_result_path: /mnt/workspace/output/qwen-1_8b/v4-20240128-154925/checkpoint-100/infer_result_20240128-155452.jsonl
[LABELS]negative
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