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llama
alignment-handbook
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replica-ourgen-heavy-barc-ttft

This model is a fine-tuned version of barc0/engineer1-heavy-barc-llama3.1-8b-ins-fft-transduction_lr1e-5_epoch3 on the tttx/test-ttft-og, the barc0/transduction_formatted_rearc_dataset_100k and the barc0/transduction_heavy_100k_jsonl datasets. It achieves the following results on the evaluation set:

  • Loss: 0.0339

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: 2
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • total_eval_batch_size: 8
  • 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
0.0344 1.0 1334 0.0371
0.0274 2.0 2668 0.0299
0.0012 3.0 4002 0.0339

Framework versions

  • PEFT 0.13.2
  • Transformers 4.45.0.dev0
  • Pytorch 2.4.0+cu121
  • Datasets 3.1.0
  • Tokenizers 0.19.1
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