---
license: gemma
base_model: google/gemma-2-2b-it
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- sardinelab/MT-pref
model-index:
- name: gemma-2-2b-it-mt-sft-full_sardine
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# gemma-2-2b-it-mt-sft-full_sardine

This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) on the sardinelab/MT-pref 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- total_eval_batch_size: 16
- 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 4.43.3
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1