Sugutt/Kalenjin-qwen2.5-7B

LoRA adapter from continued pretraining for a Kalenjin-focused language model. The adapter was trained on Modal from Qwen/Qwen2.5-7B and is intended as the CPT checkpoint before later SFT, DPO, and GRPO stages.

Model Scope

  • Base model: Qwen/Qwen2.5-7B
  • Method: QLoRA Continued Pretraining
  • Language/domain: Kalenjin-heavy text
  • Adapter only: yes
  • Training objective: causal language modeling
  • Not instruction-tuned yet
  • Not a translator yet

Contents

  • adapter/: PEFT LoRA adapter weights and config
  • tokenizer/: tokenizer saved with the CPT run
  • training_config.json: Modal CPT training configuration
  • metrics.json: training and evaluation metrics
  • evaluation_report.json: CPT adapter evaluation report, if available
  • base_evaluation_report.json: base model evaluation report, if available
  • samples.txt: qualitative generation samples

Evaluation

Held-out file: /data/processed/kalenjin_cpt_eval.jsonl

Model Eval loss Perplexity Metric
Base 5.4601 235.1302 batch mean
CPT adapter 2.7906 16.2915 batch mean

Token-weighted metrics may also be present in the JSON reports. The batch-mean metric matches the training/Trainer-style evaluation path.

Usage

from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer

base_model = "Qwen/Qwen2.5-7B"
adapter_repo = "Sugutt/Kalenjin-qwen2.5-7B"

tokenizer = AutoTokenizer.from_pretrained(adapter_repo)
model = AutoModelForCausalLM.from_pretrained(base_model, device_map="auto")
model = PeftModel.from_pretrained(model, adapter_repo)

Training Notes

{
  "model_name": "Qwen/Qwen2.5-7B",
  "train_file": "/data/processed/kalenjin_cpt_train.jsonl",
  "eval_file": "/data/processed/kalenjin_cpt_eval.jsonl",
  "output_dir": "/outputs/kalenjin-cpt",
  "max_seq_length": 2048,
  "epochs": 2.0,
  "learning_rate": 2e-05,
  "batch_size": 2,
  "grad_accum": 8,
  "lora_r": 32,
  "lora_alpha": 32,
  "lora_dropout": 0.05,
  "save_steps": 100,
  "logging_steps": 10,
  "max_steps": -1,
  "warmup_ratio": 0.03,
  "weight_decay": 0.01,
  "lr_scheduler_type": "cosine",
  "optimizer": "paged_adamw_8bit",
  "run_name": "kalenjin-cpt",
  "wandb_enabled": true,
  "wandb_project": "kalenjin-llm",
  "wandb_entity": "",
  "wandb_tags": "cpt,kalenjin,modal",
  "wandb_mode": "online"
}

This repository contains an adapter, not a merged full model.

Downloads last month
-
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for Sugutt/Kalenjin-qwen2.5-7B

Base model

Qwen/Qwen2.5-7B
Adapter
(853)
this model