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metadata
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
  - GaetanMichelet/chat-60_ft_task-3_auto
  - GaetanMichelet/chat-120_ft_task-3_auto
  - GaetanMichelet/chat-180_ft_task-3_auto
library_name: peft
license: llama3.1
tags:
  - alignment-handbook
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: Llama-31-8B_task-3_180-samples_config-2_full_auto
    results: []

Llama-31-8B_task-3_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-3_auto, the GaetanMichelet/chat-120_ft_task-3_auto and the GaetanMichelet/chat-180_ft_task-3_auto datasets. It achieves the following results on the evaluation set:

  • Loss: 1.1260

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
1.674 0.9412 8 1.6584
1.5596 2.0 17 1.5302
1.4536 2.9412 25 1.4046
1.1955 4.0 34 1.2397
1.1221 4.9412 42 1.1855
1.1181 6.0 51 1.1592
1.1246 6.9412 59 1.1434
1.0507 8.0 68 1.1335
0.9763 8.9412 76 1.1265
0.9776 10.0 85 1.1260
0.929 10.9412 93 1.1289
0.8679 12.0 102 1.1548
0.8616 12.9412 110 1.1690
0.815 14.0 119 1.2061
0.6912 14.9412 127 1.2300
0.6046 16.0 136 1.2953
0.5919 16.9412 144 1.3360

Framework versions

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