---
base_model: google/gemma-2-9b-it
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- princeton-nlp/gemma2-ultrafeedback-armorm
model-index:
- name: princeton-nlp/gemma-2-9b-it-SimPO 
  results: []
---

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# gemma2-9b-simpo-beta-10-ratio-0.4-lr-8e-7

This model is a fine-tuned version of [/scratch/gpfs/DANQIC/ym0081/hf_cache/gemma-2-9b-it](https://huggingface.co//scratch/gpfs/DANQIC/ym0081/hf_cache/gemma-2-9b-it) on the /scratch/gpfs/DANQIC/ym0081/hf_cache/gemma2-ultrafeedback-armorm/dataset_dict/ dataset.

## 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: 8e-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



### Framework versions

- Transformers 4.42.4
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1