Llama-31-8B_task-1_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-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: 0.7848

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
2.1079 0.9412 8 2.0439
1.7735 2.0 17 1.6643
1.4106 2.9412 25 1.2322
0.901 4.0 34 0.9259
0.8657 4.9412 42 0.8770
0.846 6.0 51 0.8422
0.7582 6.9412 59 0.8153
0.7203 8.0 68 0.7906
0.6598 8.9412 76 0.7848
0.5979 10.0 85 0.7954
0.5547 10.9412 93 0.8095
0.4007 12.0 102 0.8623
0.3489 12.9412 110 0.9627
0.2894 14.0 119 1.0531
0.1972 14.9412 127 1.1217
0.1682 16.0 136 1.2316

Framework versions

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