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Llama-31-8B_task-3_180-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-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: 0.3387

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
2.1694 0.9412 8 2.0003
1.1443 2.0 17 0.8652
0.5201 2.9412 25 0.4725
0.2979 4.0 34 0.3815
0.3128 4.9412 42 0.3738
0.3107 6.0 51 0.3410
0.2488 6.9412 59 0.3388
0.252 8.0 68 0.3387
0.2324 8.9412 76 0.3474
0.1655 10.0 85 0.3932
0.1782 10.9412 93 0.4127
0.0536 12.0 102 0.4492
0.0425 12.9412 110 0.5433
0.0347 14.0 119 0.6090
0.0231 14.9412 127 0.5974

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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