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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: 2.1615

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
23.7344 0.91 5 7.9584
14.6026 2.0 11 6.8289
10.8118 2.91 16 6.4185
10.8598 4.0 22 5.1061
7.9354 4.91 27 1.7011
2.0354 6.0 33 1.4461
1.4855 6.91 38 1.3565
1.326 8.0 44 1.2935
1.1375 8.91 49 1.2696
0.9091 10.0 55 1.2716
0.8111 10.91 60 1.2861
0.689 12.0 66 1.3148
0.6341 12.91 71 1.3391
0.5359 14.0 77 1.4232
0.4664 14.91 82 1.5107
0.3951 16.0 88 1.6597
0.3593 16.91 93 1.9377
0.2802 18.0 99 1.9024
0.2613 18.91 104 2.0981
0.2262 20.0 110 2.1472
0.2169 20.91 115 2.1633
0.2232 22.0 121 2.1595
0.2096 22.73 125 2.1615

Framework versions

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