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Baidicoot
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run-gemma

PEFT
Safetensors
trl
reward-trainer
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metadata
base_model: google/gemma-2b
library_name: peft
license: gemma
metrics:
  - accuracy
tags:
  - trl
  - reward-trainer
  - generated_from_trainer
model-index:
  - name: run-gemma
    results: []

run-gemma

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

  • Loss: 0.4238
  • Accuracy: 0.7778

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: 2e-05
  • train_batch_size: 64
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 20
  • training_steps: 200

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.7031 0.1087 10 0.6740 0.5752
0.6719 0.2174 20 0.6701 0.6046
0.6602 0.3261 30 0.6497 0.6601
0.6367 0.4348 40 0.6113 0.7059
0.6172 0.5435 50 0.5686 0.7320
0.5625 0.6522 60 0.5276 0.7451
0.5664 0.7609 70 0.4938 0.7451
0.5859 0.8696 80 0.4651 0.7712
0.5 0.9783 90 0.4560 0.7647
0.5898 1.0870 100 0.4560 0.7582
0.5664 1.1957 110 0.4459 0.7516
0.4648 1.3043 120 0.4387 0.7745
0.5117 1.4130 130 0.4306 0.7712
0.4219 1.5217 140 0.4239 0.7680
0.3828 1.6304 150 0.4314 0.7680
0.3789 1.7391 160 0.4319 0.7647
0.3828 1.8478 170 0.4291 0.7680
0.3438 1.9565 180 0.4279 0.7745
0.3496 2.0652 190 0.4274 0.7712
0.3945 2.1739 200 0.4238 0.7778

Framework versions

  • PEFT 0.12.0
  • Transformers 4.44.0
  • Pytorch 2.4.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1