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metadata
license: gemma
base_model: google/gemma-2-2b
tags:
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: collapse_gemma-2-2b_hs2_accumulatesubsample_iter5_sftsd0
    results: []

collapse_gemma-2-2b_hs2_accumulatesubsample_iter5_sftsd0

This model is a fine-tuned version of google/gemma-2-2b on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1651
  • Num Input Tokens Seen: 5121720

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 8e-06
  • train_batch_size: 8
  • eval_batch_size: 16
  • seed: 0
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Input Tokens Seen
No log 0 0 1.3909 0
1.4516 0.0549 5 1.2704 281728
1.2569 0.1098 10 1.1896 560496
1.1565 0.1647 15 1.1711 843552
1.0247 0.2196 20 1.1630 1124256
0.999 0.2745 25 1.1730 1405360
0.9404 0.3294 30 1.1667 1687800
0.8346 0.3844 35 1.1909 1973600
0.8733 0.4393 40 1.1780 2246208
0.7992 0.4942 45 1.1868 2527096
0.597 0.5491 50 1.1766 2813840
0.6897 0.6040 55 1.1795 3093112
0.6487 0.6589 60 1.1741 3372936
0.6013 0.7138 65 1.1733 3651336
0.6563 0.7687 70 1.1680 3931512
0.5705 0.8236 75 1.1709 4216528
0.6287 0.8785 80 1.1732 4498448
0.5377 0.9334 85 1.1693 4778952
0.6489 0.9883 90 1.1661 5063320

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.4.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1