metadata

library_name: transformers
license: gemma
base_model: google/gemma-7b
tags:
  - alignment-handbook
  - trl
  - orpo
  - generated_from_trainer
  - trl
  - orpo
  - alignment-handbook
  - generated_from_trainer
datasets:
  - silviasapora/low_quality_dpo7k
model-index:
  - name: gemma-7b-orpo-low-quality
    results: []

gemma-7b-orpo-low-quality

This model is a fine-tuned version of google/gemma-7b on the silviasapora/low_quality_dpo7k dataset. It achieves the following results on the evaluation set:

Loss: 1.5517
Rewards/chosen: -0.0554
Rewards/rejected: -0.0646
Rewards/accuracies: 0.5612
Rewards/margins: 0.0092
Logps/rejected: -1.2920
Logps/chosen: -1.1085
Logits/rejected: 268.0282
Logits/chosen: 297.1682
Nll Loss: 1.4855
Log Odds Ratio: -0.6970
Log Odds Chosen: 0.2856

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: 2
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 4
total_train_batch_size: 32
total_eval_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: inverse_sqrt
lr_scheduler_warmup_steps: 100
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen	Nll Loss	Log Odds Ratio	Log Odds Chosen
1.436	0.9955	167	1.4679	-0.0508	-0.0571	0.5468	0.0063	-1.1420	-1.0158	288.9292	318.3812	1.4121	-0.6895	0.1983
1.1098	1.9970	335	1.4451	-0.0518	-0.0579	0.5468	0.0061	-1.1581	-1.0353	286.4312	315.0296	1.3839	-0.7228	0.2105
0.5921	2.9866	501	1.5517	-0.0554	-0.0646	0.5612	0.0092	-1.2920	-1.1085	268.0282	297.1682	1.4855	-0.6970	0.2856

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 3.0.0
Tokenizers 0.19.1