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---
license: gemma
library_name: peft
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
base_model: google/gemma-7b
datasets:
- llama-duo/synth_summarize_dataset
model-index:
- name: gemma7b-summarize-gemini1.5flash-80k
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/chansung18/huggingface/runs/iqxo2rdd)
# gemma7b-summarize-gemini1.5flash-80k

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the llama-duo/synth_summarize_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0229

## 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: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 4
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.8742        | 0.9982 | 280  | 2.1938          |
| 0.7213        | 2.0    | 561  | 2.1462          |
| 0.675         | 2.9982 | 841  | 2.1484          |
| 0.6439        | 4.0    | 1122 | 2.2149          |
| 0.569         | 4.9982 | 1402 | 2.3224          |
| 0.5317        | 6.0    | 1683 | 2.4839          |
| 0.472         | 6.9982 | 1963 | 2.6540          |
| 0.4306        | 8.0    | 2244 | 2.8791          |
| 0.4106        | 8.9982 | 2524 | 3.0011          |
| 0.4021        | 9.9822 | 2800 | 3.0229          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1