license: mit
datasets:
- AmanMussa/kazakh-instruction-v1
language:
- kk
metrics:
- code_eval
pipeline_tag: text-generation
Model Card for Model ID
LLAMA2 model for Kazakh Language
Model Details
This model is from Meta LLAMA 2 parameter-efficient fine-tuning with Kazakh Language.
Model Description
- Developed by: Mussa Aman
- Model type: Question Answering.
- Language(s) (NLP): Kazakh
- License: MIT
- Finetuned from model [optional]: Meta LLAMA 2
Model Sources [optional]
Out-of-Scope Use
There are still some mistakes during the inference process.
Bias, Risks, and Limitations
The parameter size could be larger, and the dataset need to be optimized.
Training Data
Evaluation
Run summary:
train/epoch 1.0 train/global_step 3263 train/learning_rate 0.0 train/loss 0.975 train/total_flos 5.1749473473500774e+17 train/train_loss 0.38281 train/train_runtime 13086.8735 train/train_samples_per_second 3.989 train/train_steps_per_second 0.249
Environment
- Hardware Type: NVIDIA A100 40GB
- Hours used: 10 hours
- Cloud Provider: Google Colab
Citation [optional]
Citation
BibTeX:
@misc{aman_2023, author = {Aman Mussa}, title = {Self-instruct data pairs for Kazakh language}, year = {2023}, howpublished = {\url{https://huggingface.co/datasets/AmanMussa/instructions_kaz_version_1}}, }
APA:
Aman, M. (2023). Self-instruct data pairs for Kazakh language. Retrieved from https://huggingface.co/datasets/AmanMussa/instructions_kaz_version_1
Model Card Contact
Please contact in email: a_mussa@kbtu.kz