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metadata
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
  - alignment-handbook
  - generated_from_trainer
datasets:
  - trl-lib/kto-mix-14k
  - chaoweihuang/lf-response-llama3-f1_100_0.8-fg0.5
model-index:
  - name: kto-mix-14k-lf-response-llama3-f1_100_0.8-fg0.5-fgudw4.0-kto-fg
    results: []

Paper: https://huggingface.co/papers/2410.01691.

kto-mix-14k-lf-response-llama3-f1_100_0.8-fg0.5-fgudw4.0-kto-fg

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the trl-lib/kto-mix-14k and the chaoweihuang/lf-response-llama3-f1_100_0.8-fg0.5 datasets. It achieves the following results on the evaluation set:

  • Loss: 0.4110
  • Rewards/chosen: 1.7360
  • Logps/chosen: -336.0412
  • Rewards/rejected: -2.2628
  • Logps/rejected: -406.1173
  • Rewards/margins: 3.9987
  • Kl: 0.0141
  • Fg Rewards/chosen Sum: -1.5560
  • Fg Logps/policy Chosen: -6.7332
  • Fg Logps/reference Chosen: -6.0419
  • Count/fg Chosen: 30.1832
  • Fg Rewards/rejected Sum: -0.9033
  • Fg Logps/policy Rejected: -8.6269
  • Fg Logps/reference Rejected: -7.5807
  • Count/fg Rejected: 6.9239
  • Fg Logps/policy Kl: -14.7946
  • Fg Logps/reference Kl: -11.4736
  • Fg Kl: nan
  • Fg Loss: 0.7625

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: 5e-07
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • total_eval_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1.0

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Logps/chosen Rewards/rejected Logps/rejected Rewards/margins Kl Fg Rewards/chosen Sum Fg Logps/policy Chosen Fg Logps/reference Chosen Count/fg Chosen Fg Rewards/rejected Sum Fg Logps/policy Rejected Fg Logps/reference Rejected Count/fg Rejected Fg Logps/policy Kl Fg Logps/reference Kl Fg Kl Fg Loss
0.4478 0.4103 400 0.4325 1.3169 -340.2313 -1.7364 -400.8539 3.0534 0.0280 -1.3939 -6.6287 -6.0419 30.1832 -0.6768 -8.3632 -7.5807 6.9239 -13.6783 -11.4736 nan 0.7654
0.4043 0.8205 800 0.4110 1.7360 -336.0412 -2.2628 -406.1173 3.9987 0.0141 -1.5560 -6.7332 -6.0419 30.1832 -0.9033 -8.6269 -7.5807 6.9239 -14.7946 -11.4736 nan 0.7625

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1