1.7 KiB
library_name, license, base_model, tags, model-index, language
| library_name | license | base_model | tags | model-index | language | |||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| transformers | cc-by-nc-4.0 | lelapa/InkubaLM-0.4B |
|
|
|
Caracal_GPT
This model is a Continuous Pre-trained (CPT) model, adapted from lelapa/InkubaLM-0.4B on the custom dataset. In this new model we add different languages from Kenya, Uganda, South Africa, Western Africa, Somalia, Ethiopia; sub-saharan Africa.
Model description
Caracal GPT is a small causal model that can be used for fine-tuning tasks. It's goal is to be used by the represented language speaker for fine-tuning to a certain language task.
The Pre-trained LM was trained on 20+ African languages, introducing Kenyan lanugages and other languages not widely available in many datasets - Luo (luo), Kamba (kam) , Maasai (mas), Somalia (som), etc.
Intended uses & limitations
The model is to be used for fine-tuning on instruction set data for the given languages.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
- loss: 1.8
Framework versions
- Transformers 4.45.2
- Pytorch 2.11.0+cu128
- Datasets 2.21.0
- Tokenizers 0.20.3