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llama3.1-8b-closedqa-gpt4o-100k

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the llama-duo/synth_closed_qa_dataset_dedup dataset. It achieves the following results on the evaluation set:

  • Loss: 2.1008

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: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • 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
0.8026 1.0 256 2.0456
0.7532 2.0 512 2.0313
0.7198 3.0 768 2.0404
0.7053 4.0 1024 2.0419
0.6831 5.0 1280 2.0541
0.6633 6.0 1536 2.0744
0.6595 7.0 1792 2.0814
0.6374 8.0 2048 2.0939
0.6277 9.0 2304 2.0994
0.616 10.0 2560 2.1008

Framework versions

  • PEFT 0.12.0
  • Transformers 4.44.0
  • Pytorch 2.4.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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