---
license: gemma
library_name: peft
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
base_model: google/gemma-7b
datasets:
- llama-duo/synth_closed_qa_dataset_dedup
model-index:
- name: gemma7-closedqa-gpt4o-100k
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# gemma7-closedqa-gpt4o-100k

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the llama-duo/synth_closed_qa_dataset_dedup dataset.
It achieves the following results on the evaluation set:
- Loss: 5.0765

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 2
- total_train_batch_size: 24
- total_eval_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8445        | 0.9991 | 574  | 2.1107          |
| 0.784         | 2.0    | 1149 | 2.2301          |
| 0.6545        | 2.9991 | 1723 | 2.4329          |
| 0.5693        | 4.0    | 2298 | 2.7030          |
| 0.4555        | 4.9991 | 2872 | 3.1445          |
| 0.3504        | 6.0    | 3447 | 3.7197          |
| 0.2672        | 6.9991 | 4021 | 4.3078          |
| 0.2167        | 8.0    | 4596 | 4.8456          |
| 0.2037        | 8.9991 | 5170 | 5.0561          |
| 0.1899        | 9.9913 | 5740 | 5.0765          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1