metadata

library_name: transformers
license: gemma
base_model: google/gemma-7b
tags:
  - alignment-handbook
  - trl
  - orpo
  - generated_from_trainer
  - trl
  - orpo
  - generated_from_trainer
datasets:
  - silviasapora/low_quality_dpo7k
model-index:
  - name: gemma-7b-borpo-low-quality-v3
    results: []

gemma-7b-borpo-low-quality-v3

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: 2.1095
Rewards/chosen: -0.6954
Rewards/rejected: -0.8346
Rewards/accuracies: 0.5571
Rewards/margins: 0.1392
Logps/rejected: -1.6692
Logps/chosen: -1.3909
Logits/rejected: 262.5518
Logits/chosen: 319.3429
Nll Loss: 1.7836
Log Odds Ratio: -0.6395
Log Odds Chosen: 0.4455

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: 1e-05
train_batch_size: 2
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 32
total_eval_batch_size: 8
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
1.9721	1.0	168	1.9526	-0.6072	-0.7027	0.5571	0.0955	-1.4054	-1.2144	282.1215	336.2867	1.6515	-0.6573	0.2649
1.3299	2.0	336	1.9015	-0.5986	-0.6805	0.5	0.0820	-1.3611	-1.1972	293.2820	345.2333	1.5933	-0.6792	0.2173
0.6266	3.0	504	2.1095	-0.6954	-0.8346	0.5571	0.1392	-1.6692	-1.3909	262.5518	319.3429	1.7836	-0.6395	0.4455

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1