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openhermes-1b-olmo-sft-qlora

This model is a fine-tuned version of allenai/OLMo-1B-hf on the Ritvik19/open-hermes-2_5-reformatted dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4363

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0002
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 128
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
1.2568 0.9996 1523 1.4363

Framework versions

  • PEFT 0.7.1
  • Transformers 4.40.1
  • Pytorch 2.1.2+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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