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llama2-7b-sft-full-llama2

This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0380

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-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 128
  • 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: 3

Training results

Training Loss Epoch Step Validation Loss
1.0183 0.9980 126 1.0127
0.869 1.9960 252 1.0026
0.714 2.9941 378 1.0380

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0a0+ebedce2
  • Datasets 2.19.2
  • Tokenizers 0.19.1
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Dataset used to train kevin1010607/llama2-7b-sft-full-llama2