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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-1_full_auto
    results: []

Llama-31-8B_task-1_180-samples_config-1_full_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: 0.7769

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
1.9328 1.0 17 1.8837
1.3207 2.0 34 1.2487
0.8894 3.0 51 0.9027
0.8023 4.0 68 0.8472
0.7382 5.0 85 0.8033
0.6937 6.0 102 0.7769
0.6042 7.0 119 0.7946
0.4994 8.0 136 0.8584
0.3568 9.0 153 0.9741
0.2463 10.0 170 1.0730
0.1823 11.0 187 1.1565
0.1229 12.0 204 1.2557
0.1015 13.0 221 1.3300

Framework versions

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