---
license: gemma
library_name: peft
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
base_model: google/gemma-7b
datasets:
- llama-duo/synth_coding_dataset_dedup
model-index:
- name: gemma7b-coding-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. -->

# gemma7b-coding-gpt4o-100k

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the llama-duo/synth_coding_dataset_dedup dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9658

## 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: 4
- gradient_accumulation_steps: 2
- 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: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5262        | 0.9989 | 470  | 1.3224          |
| 0.4826        | 2.0    | 941  | 1.3435          |
| 0.4369        | 2.9989 | 1411 | 1.4787          |
| 0.3819        | 4.0    | 1882 | 1.7432          |
| 0.3345        | 4.9989 | 2352 | 2.1234          |
| 0.2875        | 6.0    | 2823 | 2.5846          |
| 0.2319        | 6.9989 | 3293 | 3.1057          |
| 0.1968        | 8.0    | 3764 | 3.6609          |
| 0.1809        | 8.9989 | 4234 | 3.9400          |
| 0.1757        | 9.9894 | 4700 | 3.9658          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.40.1
- Pytorch 2.2.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1