metadata

license: apache-2.0
base_model: Qwen/Qwen2-1.5B-Instruct
tags:
  - alignment-handbook
  - trl
  - dpo
  - generated_from_trainer
  - trl
  - dpo
  - generated_from_trainer
datasets:
  - princeton-nlp/llama3-ultrafeedback
model-index:
  - name: qwen2-1.5b-instruct-simpo-lr-5e-07-gamma-1.5
    results: []

Description

This model was trained as part of the Reinforcement Learning - 24 project at Peking University, focusing on [simpo].

Authors

Ejafa Bassam
Yaroslav Ponomarenko

qwen2-1.5b-instruct-simpo-lr-5e-07-gamma-1.5

This model is a fine-tuned version of Qwen/Qwen2-1.5B-Instruct on the princeton-nlp/llama3-ultrafeedback dataset. It achieves the following results on the evaluation set:

Loss: 1.6346
Rewards/chosen: -2.6152
Rewards/rejected: -2.7999
Rewards/accuracies: 0.5685
Rewards/margins: 0.1847
Logps/rejected: -1.1200
Logps/chosen: -1.0461
Logits/rejected: -1.5578
Logits/chosen: -1.5356

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: 2
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 8
total_train_batch_size: 128
total_eval_batch_size: 32
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
1.6402	0.8549	400	1.6353	-2.6155	-2.7990	0.5726	0.1835	-1.1196	-1.0462	-1.5085	-1.4841

Framework versions

Transformers 4.41.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1