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metadata
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
  - GaetanMichelet/chat-60_ft_task-2_auto
  - GaetanMichelet/chat-120_ft_task-2_auto
  - GaetanMichelet/chat-180_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_180-samples_config-2_full_auto
    results: []

Llama-31-8B_task-2_180-samples_config-2_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-2_auto, the GaetanMichelet/chat-120_ft_task-2_auto and the GaetanMichelet/chat-180_ft_task-2_auto datasets. It achieves the following results on the evaluation set:

  • Loss: 1.0008

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
1.4945 0.9412 8 1.4964
1.3936 2.0 17 1.3700
1.2937 2.9412 25 1.2535
1.0479 4.0 34 1.1012
0.9934 4.9412 42 1.0544
0.9927 6.0 51 1.0315
0.9944 6.9412 59 1.0179
0.9293 8.0 68 1.0085
0.8712 8.9412 76 1.0033
0.8604 10.0 85 1.0008
0.8278 10.9412 93 1.0047
0.7609 12.0 102 1.0211
0.7599 12.9412 110 1.0358
0.7215 14.0 119 1.0646
0.6195 14.9412 127 1.0861
0.5401 16.0 136 1.1417
0.5303 16.9412 144 1.1947

Framework versions

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