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metadata
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: Llama-31-8B_task-1_120-samples_config-1_full_auto
    results: []

Llama-31-8B_task-1_120-samples_config-1_full_auto

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3713

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: 0.0001
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 8
  • total_train_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: 50

Training results

Training Loss Epoch Step Validation Loss
2.1444 1.0 11 1.9951
1.5597 2.0 22 1.5854
1.1135 3.0 33 1.0142
0.8595 4.0 44 0.8794
0.7701 5.0 55 0.8356
0.7434 6.0 66 0.8024
0.6039 7.0 77 0.7895
0.5441 8.0 88 0.7838
0.4965 9.0 99 0.8283
0.353 10.0 110 0.9092
0.2505 11.0 121 1.0033
0.2204 12.0 132 1.1738
0.1355 13.0 143 1.3070
0.1041 14.0 154 1.3560
0.0759 15.0 165 1.3713

Framework versions

  • PEFT 0.12.0
  • Transformers 4.44.0
  • Pytorch 2.1.2+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1