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metadata
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
  - GaetanMichelet/chat-60_ft_task-1_auto
  - GaetanMichelet/chat-120_ft_task-1_auto
  - GaetanMichelet/chat-180_ft_task-1_auto
library_name: peft
license: llama3.1
tags:
  - alignment-handbook
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: Llama-31-8B_task-1_180-samples_config-2_auto
    results: []

Llama-31-8B_task-1_180-samples_config-2_auto

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the GaetanMichelet/chat-60_ft_task-1_auto, the GaetanMichelet/chat-120_ft_task-1_auto and the GaetanMichelet/chat-180_ft_task-1_auto datasets. It achieves the following results on the evaluation set:

  • Loss: 0.8755

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
1.178 0.9412 8 1.1844
0.9678 2.0 17 1.0291
0.9547 2.9412 25 0.9495
0.8037 4.0 34 0.8970
0.7404 4.9412 42 0.8755
0.6681 6.0 51 0.9058
0.4752 6.9412 59 0.9785
0.3663 8.0 68 1.0201
0.2328 8.9412 76 1.2509
0.1375 10.0 85 1.4120
0.1013 10.9412 93 1.4669
0.0523 12.0 102 1.5482

Framework versions

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