engineer-heavy-500k-barc-llama3.1-8b-ins-fft-induction_lr1e-5_epoch3-1122

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the barc0/induction_heavy_100k_jsonl, the barc0/induction_heavy_suggestfunction_100k_jsonl, the barc0/induction_100k_gpt4o-mini_generated_problems_seed100.jsonl_messages_format_0.3 and the barc0/induction_100k-gpt4-description-gpt4omini-code_generated_problems_messages_format_0.3 datasets. It achieves the following results on the evaluation set:

  • Loss: 0.2710

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 128
  • total_eval_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: 2

Training results

Training Loss Epoch Step Validation Loss
0.2795 1.0 2995 0.2817
0.239 2.0 5990 0.2710

Framework versions

  • Transformers 4.45.0.dev0
  • Pytorch 2.4.0
  • Datasets 3.1.0
  • Tokenizers 0.19.1
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