hugodk-sch's picture
Model save
1aff0c5 verified
|
raw
history blame
2.52 kB
metadata
license: apache-2.0
library_name: peft
tags:
  - trl
  - dpo
  - generated_from_trainer
base_model: norallm/normistral-7b-warm
model-index:
  - name: ap-normistral-7b-align-scan
    results: []

ap-normistral-7b-align-scan

This model is a fine-tuned version of norallm/normistral-7b-warm on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7290
  • Rewards/chosen: -0.1187
  • Rewards/rejected: -0.1591
  • Rewards/accuracies: 0.5453
  • Rewards/margins: 0.0404
  • Logps/rejected: -36.2848
  • Logps/chosen: -32.6805
  • Logits/rejected: 98.5351
  • Logits/chosen: 98.5572

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-06
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 2
  • 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: 1

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.6859 0.26 100 0.7229 -0.0559 -0.0850 0.5282 0.0290 -36.1364 -32.5550 98.6727 98.6826
0.5453 0.52 200 0.7068 -0.1291 -0.2159 0.5332 0.0868 -36.3984 -32.7014 98.4732 98.4956
0.5511 0.78 300 0.7290 -0.1187 -0.1591 0.5453 0.0404 -36.2848 -32.6805 98.5351 98.5572

Framework versions

  • PEFT 0.10.0
  • Transformers 4.39.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.15.1