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induction-run4-gpt4omini-20k-100seeds-barc-llama3.1-8b-instruct-lora64_lr2e-4_epoch3

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the barc0/induction_20k_gpt4o-mini_generated_problems_seed100.jsonl_messages_format_0.3 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3360

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: 4
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • total_eval_batch_size: 32
  • 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
0.3484 0.9966 145 0.3561
0.3202 2.0 291 0.3388
0.3107 2.9897 435 0.3360

Framework versions

  • PEFT 0.13.0
  • Transformers 4.45.0.dev0
  • Pytorch 2.4.0+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1
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