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metadata
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
  - GaetanMichelet/chat-60_ft_task-2_auto
library_name: peft
license: llama3.1
tags:
  - alignment-handbook
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: Llama-31-8B_task-2_60-samples_config-2_auto
    results: []

Llama-31-8B_task-2_60-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-2_auto dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5986

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
0.8574 0.6957 2 0.8904
0.8746 1.7391 5 0.8490
0.7842 2.7826 8 0.7717
0.728 3.8261 11 0.7140
0.6405 4.8696 14 0.6587
0.5991 5.9130 17 0.6365
0.5371 6.9565 20 0.6147
0.5007 8.0 23 0.6018
0.4783 8.6957 25 0.5986
0.4118 9.7391 28 0.6050
0.4002 10.7826 31 0.6278
0.3234 11.8261 34 0.6697
0.2816 12.8696 37 0.7073
0.2159 13.9130 40 0.7197
0.1785 14.9565 43 0.7951
0.1209 16.0 46 0.9001

Framework versions

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