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metadata
license: gemma
library_name: peft
tags:
  - alignment-handbook
  - trl
  - sft
  - generated_from_trainer
base_model: google/gemma-2b
datasets:
  - llama-duo/synth_summarize_dataset_dedup
model-index:
  - name: gemma2b-summarize-gpt4o-64k
    results: []

gemma2b-summarize-gpt4o-64k

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

  • Loss: 2.5990

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: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 3
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 48
  • total_eval_batch_size: 24
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss
1.2959 1.0 146 2.5295
1.1524 2.0 292 2.4913
1.1138 3.0 438 2.4847
1.0703 4.0 584 2.4927
1.0423 5.0 730 2.5080
1.0322 6.0 876 2.5202
1.0113 7.0 1022 2.5385
0.9857 8.0 1168 2.5522
0.9865 9.0 1314 2.5657
0.9691 10.0 1460 2.5774
0.952 11.0 1606 2.5889
0.97 12.0 1752 2.5957
0.9514 13.0 1898 2.5988
0.9469 14.0 2044 2.5997
0.9469 15.0 2190 2.5990

Framework versions

  • PEFT 0.11.1
  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1