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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-claude3sonnet-30k
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/7bdtvabz)
# gemma7b-summarize-claude3sonnet-30k
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: 3.0044
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0072 | 1.0 | 148 | 2.2672 |
| 0.8705 | 2.0 | 296 | 2.1745 |
| 0.7957 | 3.0 | 444 | 2.1914 |
| 0.731 | 4.0 | 592 | 2.2511 |
| 0.634 | 5.0 | 740 | 2.3409 |
| 0.5418 | 6.0 | 888 | 2.4841 |
| 0.4578 | 7.0 | 1036 | 2.6822 |
| 0.3886 | 8.0 | 1184 | 2.8497 |
| 0.3611 | 9.0 | 1332 | 2.9868 |
| 0.3501 | 10.0 | 1480 | 3.0044 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |