llama-39m

Toy LLaMA-39M

• This is a tiny LLaMA model pretrained on Recag/Rp_C4_55, a small subset of C4 with seq_len=512.

  • Model architecture

    {
      "hidden_size": 512,
      "intermediate_size": 2048,
      "max_position_embeddings": 2048,
      "num_attention_heads": 8,
      "num_hidden_layers": 2,
      "num_key_value_heads": 8
    }
    

  • Load model and tokenizer:

    from transformers import AutoTokenizer, AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("Cheng98/llama-39m")
    tokenizer = AutoTokenizer.from_pretrained("Cheng98/llama-39m")
    

  • Training script: huggingface/transformers/examples/pytorch/language-modeling/run_clm.py

    # "train" split is created from the last 95% samples of original "train" subset
    raw_datasets["validation"] = load_dataset("Recag/Rp_C4_55", split="train[5%:]")
    

• Evaluation (seq_len=512):

  Dataset	Eval loss	Perplexity	Accuracy	block_size
  Recag/Rp_C4_55	3.63	37.78	0.3561	512
  Wikitext2	4.58	97.48	0.2719	512

  • Evaluation command (Wikitext2):

    # Evaluation command
    python run_clm.py --model_name_or_path Cheng98/llama-39m \
      --dataset_name wikitext \
      --dataset_config_name wikitext-2-raw-v1 \
      --block_size 512 \
      --do_eval \
      --output_dir ./results
    

  • Evaluation on Recag/Rp_C4_55 (seq_len=512):

    # "validation" split is created from the first 5% samples of original "train" subset
    raw_datasets["validation"] = load_dataset("Recag/Rp_C4_55", split="train[:5%]")
    

    Results

    {
      "eval_accuracy": 0.3561766818954313,
      "eval_loss": 3.6318140029907227,
      "eval_runtime": 190.8411,
      "eval_samples": 19413,
      "eval_samples_per_second": 101.723,
      "eval_steps_per_second": 1.593,
      "perplexity": 37.7812898658763
    }
    

  • Evaluation on Wikitext2 (seq_len=512):

    {
      "eval_accuracy": 0.2718795201225219,
      "eval_loss": 4.579628944396973,
      "eval_runtime": 3.939,
      "eval_samples": 575,
      "eval_samples_per_second": 145.976,
      "eval_steps_per_second": 0.762,
      "perplexity": 97.47821765687856
    }