BEE-spoke-data / verysmol_llama-v11-KIx2

huggingface.co
Total runs: 97
24-hour runs: -2
7-day runs: -52
30-day runs: -63
Model's Last Updated: December 29 2025
text-generation

Introduction of verysmol_llama-v11-KIx2

Model Details of verysmol_llama-v11-KIx2

verysmol_llama-v11-KIx2

Model description

This model is a fine-tuned version of v10 (refinedweb-3m dedup) further trained for 2 epochs on KI dataset.

It achieves the following results on the evaluation set:

  • Loss: 2.8876
  • Accuracy: 0.4502

evals

hf-causal-experimental (pretrained=pszemraj/verysmol_llama-v11-KIx2,revision=main,trust_remote_code=True,dtype='float'), limit: None, provide_description: False, num_fewshot: 0, batch_size: 16

Task Version Metric Value Stderr
arc_easy 0 acc 0.4024 ± 0.0101
acc_norm 0.3788 ± 0.0100
boolq 1 acc 0.6199 ± 0.0085
lambada_openai 0 ppl 111.9939 ± 4.6906
acc 0.2354 ± 0.0059
openbookqa 0 acc 0.1440 ± 0.0157
acc_norm 0.2760 ± 0.0200
piqa 0 acc 0.5713 ± 0.0115
acc_norm 0.5664 ± 0.0116
winogrande 0 acc 0.5201 ± 0.0140
Task Version Metric Value Stderr
arc_challenge 0 acc 0.1971 ± 0.0116
acc_norm 0.2278 ± 0.0123
Task Version Metric Value Stderr
hellaswag 0 acc 0.2618 ± 0.0088
acc_norm 0.2797 ± 0.0090
Task Version Metric Value Stderr
truthfulqa_mc 1 mc1 0.2509 ± 0.0152
mc2 0.4492 ± 0.0156

Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.00014
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 17514
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-06
  • lr_scheduler_type: inverse_sqrt
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 2.0
Training results
Training Loss Epoch Step Validation Loss Accuracy
3.0681 0.03 150 3.0689 0.4259
3.0113 0.07 300 3.0433 0.4278
2.9468 0.1 450 3.0362 0.4288
3.0162 0.13 600 3.0148 0.4326
2.9531 0.17 750 3.0012 0.4341
2.9282 0.2 900 2.9923 0.4358
2.9485 0.23 1050 2.9845 0.4357
2.9365 0.27 1200 2.9749 0.4375

...

Training Loss Epoch Step Validation Loss Accuracy
2.8215 1.7 7650 2.8943 0.4496
2.7714 1.74 7800 2.8914 0.4501
2.8132 1.77 7950 2.8913 0.4500
2.8505 1.8 8100 2.8906 0.4502
2.8294 1.84 8250 2.8901 0.4502
2.7977 1.87 8400 2.8891 0.4499
2.7501 1.9 8550 2.8878 0.4505
2.8038 1.94 8700 2.8883 0.4504
2.7547 1.97 8850 2.8876 0.4502

Runs of BEE-spoke-data verysmol_llama-v11-KIx2 on huggingface.co

97
Total runs
-2
24-hour runs
0
3-day runs
-52
7-day runs
-63
30-day runs

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