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gemma-7b-sft-full-longest-1k-v0

This model is a fine-tuned version of google/gemma-7b on the HuggingFaceH4/OpenHermes-2.5-1k-longest dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7445

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-06
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss
5.6993 1.0 6 2.8191
3.3379 2.0 12 2.2503
2.8978 3.0 18 2.0730
2.7495 4.0 24 1.9771
2.5265 5.0 30 1.9129
2.4727 6.0 36 1.8681
2.443 7.0 42 1.8344
2.3432 8.0 48 1.8083
2.3291 9.0 54 1.7878
2.2843 10.0 60 1.7719
2.2529 11.0 66 1.7595
2.2723 12.0 72 1.7509
2.2302 13.0 78 1.7465
2.2224 14.0 84 1.7448
2.2309 15.0 90 1.7445

Framework versions

  • Transformers 4.39.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.1
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Dataset used to train lewtun/gemma-7b-sft-full-longest-1k-v0