llama-3.2-3b-sft / README.md
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metadata
library_name: transformers
license: llama3.2
base_model: tanliboy/llama-3.2-3b
tags:
  - alignment-handbook
  - trl
  - sft
  - generated_from_trainer
  - trl
  - sft
  - alignment-handbook
  - generated_from_trainer
datasets:
  - tanliboy/OpenHermes-2.5-reformat
model-index:
  - name: llama-3.2-3b-sft
    results: []

llama-3.2-3b-sft

This model is a fine-tuned version of tanliboy/llama-3.2-3b on the tanliboy/OpenHermes-2.5-reformat dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7216

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: 3e-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
0.8741 0.0448 100 0.8600
0.8038 0.0897 200 0.8095
0.7937 0.1345 300 0.7789
0.7712 0.1794 400 0.7644
0.7393 0.2242 500 0.7565
0.7458 0.2691 600 0.7506
0.7694 0.3139 700 0.7458
0.713 0.3587 800 0.7422
0.7347 0.4036 900 0.7387
0.7243 0.4484 1000 0.7356
0.7161 0.4933 1100 0.7331
0.7247 0.5381 1200 0.7308
0.7477 0.5830 1300 0.7288
0.7429 0.6278 1400 0.7273
0.7317 0.6726 1500 0.7256
0.7226 0.7175 1600 0.7243
0.695 0.7623 1700 0.7234
0.7167 0.8072 1800 0.7226
0.686 0.8520 1900 0.7221
0.7214 0.8969 2000 0.7218
0.7358 0.9417 2100 0.7216
0.7259 0.9865 2200 0.7216

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1