初始化项目，由ModelHub XC社区提供模型

Model: theophilusowiti/Caracal_GPT
Source: Original Platform

README.md

@@ -0,0 +1,73 @@
+---
+library_name: transformers
+license: cc-by-nc-4.0
+base_model: lelapa/InkubaLM-0.4B
+tags:
+- generated_from_trainer
+model-index:
+- name: Caracal_LM
+  results: []
+language:
+- en
+- sw
+- yo
+- so
+- ln
+- ki
+- rw
+- xh
+- ha
+- luo
+- kam
+- lug
+- mas
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# Caracal_GPT
+
+This model is a Continuous Pre-trained (CPT) model, adapted from [lelapa/InkubaLM-0.4B](https://huggingface.co/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