English
This model translates Traditional Chinese sentences into English, with a focus on understanding Taiwanese-style Traditional Chinese and producing more accurate English translations.
from transformers import pipeline
model_checkpoint = "agentlans/zhtw-en"
translator = pipeline("translation", model=model_checkpoint)
# From Chinese Wikipedia's article of the day (摘自中文維基百科的今日文章)
translator("《阿奇大戰鐵血戰士》是2015年4至7月黑馬漫畫和阿奇漫畫在美國發行的四期限量連環漫畫圖書,由亞歷克斯·德坎皮創作,費爾南多·魯伊斯繪圖,屬跨公司跨界作品。")[0]['translation_text']
# Output (輸出)# Acer's Iron Blood Fighter is a four-year series of comic books published in the United States by Black Horse and Ah Chi comics from April to July of that year. The book was created by Alexander d'Campie and painted by Philnanto Ruiz. It is a cross-firm work.# Compare with my own gold standard translation: (與我自己的黃金標準翻譯比較:)# "Archie vs. Predator" is a limited four-issue comic book series published by Black Horse and Archie Comics from April to July 2015. It was created by Alex de Campi and drawn by Fernando Ruiz. It's a crossover work.
Training Procedure
Training Hyperparameters
The following hyperparameters were used during training:
Learning Rate:
5e-05
Train Batch Size:
8
Eval Batch Size:
8
Seed:
42
Optimizer:
adamw_torch with betas=(0.9,0.999) and epsilon=1e-08
LR Scheduler Type:
linear
Number of Epochs:
3.0
Training Results
Click here to see the training and validation losses
Training Loss
Epoch
Step
Validation Loss
Input Tokens Seen
3.2254
0.0804
2500
2.9105
1493088
3.0946
0.1608
5000
2.8305
2990968
3.0473
0.2412
7500
2.7737
4477792
2.9633
0.3216
10000
2.7307
5967560
2.9355
0.4020
12500
2.6843
7463192
2.9076
0.4824
15000
2.6587
8950264
2.8714
0.5628
17500
2.6304
10443344
2.8716
0.6433
20000
2.6025
11951096
2.7989
0.7237
22500
2.5822
13432464
2.7941
0.8041
25000
2.5630
14919424
2.7692
0.8845
27500
2.5497
16415080
2.757
0.9649
30000
2.5388
17897832
2.7024
1.0453
32500
2.6006
19384812
2.7248
1.1257
35000
2.6042
20876844
2.6764
1.2061
37500
2.5923
22372340
2.6854
1.2865
40000
2.5793
23866100
2.683
1.3669
42500
2.5722
25348084
2.6871
1.4473
45000
2.5538
26854100
2.6551
1.5277
47500
2.5443
28332612
2.661
1.6081
50000
2.5278
29822156
2.6497
1.6885
52500
2.5266
31319476
2.6281
1.7689
55000
2.5116
32813220
2.6067
1.8494
57500
2.5047
34298052
2.6112
1.9298
60000
2.4935
35783604
2.5207
2.0102
62500
2.4946
37281092
2.4799
2.0906
65000
2.4916
38768588
2.4727
2.1710
67500
2.4866
40252972
2.4719
2.2514
70000
2.4760
41746300
2.4738
2.3318
72500
2.4713
43241188
2.4629
2.4122
75000
2.4630
44730244
2.4524
2.4926
77500
2.4575
46231060
2.435
2.5730
80000
2.4553
47718964
2.4621
2.6534
82500
2.4475
49209724
2.4492
2.7338
85000
2.4440
50712980
2.4536
2.8142
87500
2.4394
52204380
2.4148
2.8946
90000
2.4360
53695620
2.4243
2.9750
92500
2.4350
55190020
Framework Versions
Transformers 4.48.1
Pytorch 2.3.0+cu121
Datasets 3.2.0
Tokenizers 0.21.0
Runs of agentlans zhtw-en on huggingface.co
23
Total runs
-2
24-hour runs
1
3-day runs
3
7-day runs
16
30-day runs
More Information About zhtw-en huggingface.co Model
zhtw-en huggingface.co is an AI model on huggingface.co that provides zhtw-en's model effect (), which can be used instantly with this agentlans zhtw-en model. huggingface.co supports a free trial of the zhtw-en model, and also provides paid use of the zhtw-en. Support call zhtw-en model through api, including Node.js, Python, http.
zhtw-en huggingface.co is an online trial and call api platform, which integrates zhtw-en's modeling effects, including api services, and provides a free online trial of zhtw-en, you can try zhtw-en online for free by clicking the link below.
agentlans zhtw-en online free url in huggingface.co:
zhtw-en is an open source model from GitHub that offers a free installation service, and any user can find zhtw-en on GitHub to install. At the same time, huggingface.co provides the effect of zhtw-en install, users can directly use zhtw-en installed effect in huggingface.co for debugging and trial. It also supports api for free installation.