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metadata
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
  - GaetanMichelet/chat-60_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_60-samples_config-1_auto
    results: []

Llama-31-8B_task-3_60-samples_config-1_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 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3500

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
2.1804 0.8696 5 2.1300
1.7781 1.9130 11 1.3089
0.7143 2.9565 17 0.5687
0.3741 4.0 23 0.4144
0.2554 4.8696 28 0.3896
0.2567 5.9130 34 0.3594
0.2394 6.9565 40 0.3500
0.3262 8.0 46 0.3681
0.204 8.8696 51 0.4215
0.1772 9.9130 57 0.4067
0.1163 10.9565 63 0.4379
0.062 12.0 69 0.5497
0.0248 12.8696 74 0.6054
0.0184 13.9130 80 0.6328

Framework versions

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