dehanalkautsar / gpt2-mi-wikimulti

huggingface.co
Total runs: 664
24-hour runs: 8
7-day runs: 76
30-day runs: 405
Model's Last Updated: September 25 2026
text-generation

Introduction of gpt2-mi-wikimulti

Model Details of gpt2-mi-wikimulti

GPT-2 Minangkabau WikiMulti

GPT-2-small model pretrained from scratch on the Minangkabau portion of WikiMulti.

Dataset
  • Dataset: dehanalkautsar/WikiMulti
  • File: 20260801_mi_wiki.parquet
  • Training field: text
Architecture

Standard GPT-2-small architecture:

  • Layers: 12
  • Hidden size: 768
  • Attention heads: 12
  • Maximum context: 1024
  • Vocabulary size: 50257

All GPT-2 weights were initialized from scratch.

No pretrained GPT-2 model weights were used.

Tokenizer

A separate Byte-Level BPE tokenizer was trained from scratch using only the Minangkabau training split.

The original English GPT-2 vocabulary and BPE merge rules were not used.

Vocabulary size: 50257

Training
  • GPU: NVIDIA RTX A6000
  • Precision: FP16
  • TF32: True
  • Maximum epochs: 50
  • Batch size per GPU: 8
  • Gradient accumulation: 4
  • Sequence length: 1024
  • Learning rate: 5e-05
  • Scheduler: linear
  • Validation frequency: every 500 optimizer steps
  • Early stopping patience: 3
  • Early stopping threshold: 0.0
  • Random seed: 42

Training was stopped after validation loss failed to improve for 3 consecutive evaluation rounds, unless the maximum epoch ceiling was reached first.

Best Model

Best validation loss:

1.6707736253738403

Final best-model validation loss:

1.6707736253738403

Perplexity:

5.316279015045347

Runs of dehanalkautsar gpt2-mi-wikimulti on huggingface.co

664
Total runs
8
24-hour runs
29
3-day runs
76
7-day runs
405
30-day runs

More Information About gpt2-mi-wikimulti huggingface.co Model

gpt2-mi-wikimulti huggingface.co

gpt2-mi-wikimulti huggingface.co is an AI model on huggingface.co that provides gpt2-mi-wikimulti's model effect (), which can be used instantly with this dehanalkautsar gpt2-mi-wikimulti model. huggingface.co supports a free trial of the gpt2-mi-wikimulti model, and also provides paid use of the gpt2-mi-wikimulti. Support call gpt2-mi-wikimulti model through api, including Node.js, Python, http.

dehanalkautsar gpt2-mi-wikimulti online free

gpt2-mi-wikimulti huggingface.co is an online trial and call api platform, which integrates gpt2-mi-wikimulti's modeling effects, including api services, and provides a free online trial of gpt2-mi-wikimulti, you can try gpt2-mi-wikimulti online for free by clicking the link below.

dehanalkautsar gpt2-mi-wikimulti online free url in huggingface.co:

https://huggingface.co/dehanalkautsar/gpt2-mi-wikimulti

gpt2-mi-wikimulti install

gpt2-mi-wikimulti is an open source model from GitHub that offers a free installation service, and any user can find gpt2-mi-wikimulti on GitHub to install. At the same time, huggingface.co provides the effect of gpt2-mi-wikimulti install, users can directly use gpt2-mi-wikimulti installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

gpt2-mi-wikimulti install url in huggingface.co:

https://huggingface.co/dehanalkautsar/gpt2-mi-wikimulti

Url of gpt2-mi-wikimulti

Provider of gpt2-mi-wikimulti huggingface.co

dehanalkautsar
ORGANIZATIONS

Other API from dehanalkautsar