BEE-spoke-data/NanoLlama-GQA-L10-A32_KV8-v13-KI

note that training still WIP

This model is a fine-tuned version of BEE-spoke-data/NanoLlama-GQA-L10-A32_KV8-v12-minipile on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.5937
  • Accuracy: 0.4948

Training and evaluation data

KI dataset

hf-causal-experimental (pretrained=BEE-spoke-data/NanoLlama-GQA-L10-A32_KV8-v13-KI,revision=main,trust_remote_code=True,dtype='float'), limit: None, provide_description: False, num_fewshot: 0, batch_size: 8

Task Version Metric Value Stderr
arc_easy 0 acc 0.4322 ± 0.0102
acc_norm 0.3960 ± 0.0100
boolq 1 acc 0.6196 ± 0.0085
lambada_openai 0 ppl 61.6595 ± 2.4362
acc 0.2779 ± 0.0062
openbookqa 0 acc 0.1540 ± 0.0162
acc_norm 0.2840 ± 0.0202
piqa 0 acc 0.6028 ± 0.0114
acc_norm 0.6028 ± 0.0114
winogrande 0 acc 0.5193 ± 0.0140

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.00025
  • train_batch_size: 8
  • eval_batch_size: 4
  • seed: 2280
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
  • lr_scheduler_type: inverse_sqrt
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 1.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.5744 0.08 200 2.7138 0.4776
2.5387 0.16 400 2.6713 0.4836
2.4718 0.23 600 2.6462 0.4873
2.4681 0.31 800 2.6328 0.4892
2.5351 0.39 1000 2.6227 0.4908
2.5316 0.47 1200 2.6159 0.4914
2.527 0.54 1400 2.6103 0.4921
2.4838 0.62 1600 2.6058 0.4930
2.4483 0.7 1800 2.6024 0.4934
2.426 0.78 2000 2.5998 0.4937
2.4685 0.86 2200 2.5961 0.4944
2.4473 0.93 2400 2.5937 0.4948

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 2.1.0
  • Datasets 2.15.0
  • Tokenizers 0.15.0

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 29.23
AI2 Reasoning Challenge (25-Shot) 23.81
HellaSwag (10-Shot) 29.39
MMLU (5-Shot) 25.37
TruthfulQA (0-shot) 44.77
Winogrande (5-shot) 51.14
GSM8k (5-shot) 0.91
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Evaluation results