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metadata
license: gemma
library_name: peft
tags:
  - alignment-handbook
  - trl
  - sft
  - generated_from_trainer
base_model: google/gemma-7b
datasets:
  - chansung/no_robots_only_coding
model-index:
  - name: gemma-7b-sft-qlora-1
    results: []

gemma-7b-sft-qlora-1

This model is a fine-tuned version of google/gemma-7b on the chansung/no_robots_only_coding dataset. It achieves the following results on the evaluation set:

  • Loss: 2.2095

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: 0.0002
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • total_eval_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss
23.6212 0.91 5 8.0020
14.6688 2.0 11 6.8099
10.8277 2.91 16 6.4585
10.965 4.0 22 5.2759
8.3233 4.91 27 1.6939
2.2795 6.0 33 1.4540
1.5047 6.91 38 1.3612
1.3243 8.0 44 1.2886
1.1264 8.91 49 1.2783
0.9122 10.0 55 1.2740
0.8184 10.91 60 1.2854
0.6918 12.0 66 1.3135
0.6194 12.91 71 1.3431
0.5176 14.0 77 1.4737
0.4514 14.91 82 1.7112
0.3759 16.0 88 1.8429
0.3464 16.91 93 1.8994
0.2681 18.0 99 1.9583
0.2487 18.91 104 2.1623
0.2122 20.0 110 2.2136
0.2036 20.91 115 2.2150
0.2098 22.0 121 2.2189
0.1955 22.73 125 2.2095

Framework versions

  • PEFT 0.7.1
  • Transformers 4.39.3
  • Pytorch 2.2.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2