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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-3_120-samples_config-2_full
    results: []

Llama-31-8B_task-3_120-samples_config-2_full

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: 1.2296

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: 16
  • total_train_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: 50

Training results

Training Loss Epoch Step Validation Loss
1.7269 0.9091 5 1.6901
1.6699 2.0 11 1.5939
1.5273 2.9091 16 1.5005
1.3953 4.0 22 1.3805
1.2642 4.9091 27 1.2621
1.1571 6.0 33 1.1986
1.1345 6.9091 38 1.1788
1.1145 8.0 44 1.1606
1.0654 8.9091 49 1.1505
1.0821 10.0 55 1.1417
1.0346 10.9091 60 1.1381
1.0027 12.0 66 1.1336
0.9693 12.9091 71 1.1350
0.9594 14.0 77 1.1414
0.8512 14.9091 82 1.1548
0.863 16.0 88 1.1607
0.8028 16.9091 93 1.1746
0.731 18.0 99 1.2033
0.7089 18.9091 104 1.2296

Framework versions

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