How to get started fine-tuning a transformer model on my own dataset?

Beginners
1

How can I take a pre-trained AI model from Hugging Face and train it on my own data so it learns my specific task?

2 Likes
2

Try courses.

1 Like
3

I used Claude to generate training code and Kaggle for compute. They give you 30 GPU hours per week for free.

1 Like
4

To Fine-tunine a Hugging Face model on your data

  1. Pick a base: e.g., mistralai/Mistral-7B-Instruct or meta-llama/Llama-3.1-8B-Instruct. On modest GPUs, use LoRA/QLoRA (PEFT + bitsandbytes).

  2. Format data: for SFT, a simple schema is {"instruction": "...", "response": "..."} (train/eval JSONL).

  3. Train (TRL SFT):

    from trl import SFTTrainer, SFTConfig
    from transformers import AutoModelForCausalLM, AutoTokenizer
    from peft import LoraConfig, get_peft_model

    name=“mistralai/Mistral-7B-Instruct-v0.3”
    tok = AutoTokenizer.from_pretrained(name)
    model = AutoModelForCausalLM.from_pretrained(name, device_map=“auto”)
    model = get_peft_model(model, LoraConfig(r=16, lora_alpha=32, target_modules=[“q_proj”,“v_proj”]))
    cfg=SFTConfig(output_dir=“./out”, per_device_train_batch_size=4, num_train_epochs=2)
    trainer=SFTTrainer(model=model, tokenizer=tok, train_dataset=train_ds, eval_dataset=eval_ds, dataset_text_field=“text”, args=cfg)
    trainer.train(); trainer.save_model(“./out/final”)

You can do the same faster with RapidFire AI (if you want speed + control):

Launch many configs in parallel (models, LR, LoRA ranks), and stop / resume / clone-modify / warm-start runs mid-training with a built-in dashboard (MLflow under the hood).

Minimal flow:

pip install rapidfireai
rapidfireai init && rapidfireai start


from rapidfireai import Experiment
# define a few RFModelConfig variants (different models/LR/LoRA); then:
Experiment("my-exp").run_fit(config_group, create_model, train_ds, eval_ds, num_chunks=4)

Use this method, when you’re exploring to find the best setup quickly or iterating live under tight GPU budgets.

Disclosure: I work for RapidFire AI.

1 Like