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gemma7b-summarize-gpt4o-16k

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

  • Loss: 2.6528

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: 4
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss
19.7993 0.9818 27 7.7915
2.9592 2.0 55 3.8534
1.6171 2.9818 82 2.8793
1.3574 4.0 110 2.7211
1.2908 4.9818 137 2.6808
1.2355 6.0 165 2.6636
1.2095 6.9818 192 2.6539
1.1869 8.0 220 2.6529
1.1877 8.9818 247 2.6520
1.1898 9.8182 270 2.6528

Framework versions

  • PEFT 0.10.0
  • Transformers 4.40.0
  • Pytorch 2.1.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.19.1
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Dataset used to train llama-duo/gemma7b-summarize-gpt4o-16k