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---
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- llama-duo/synth_summarize_dataset_dedup
base_model: google/gemma-7b
model-index:
- name: gemma7b-summarize-claude3sonnet-32k
  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-summarize-claude3sonnet-32k

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the llama-duo/synth_summarize_dataset_dedup dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5524

## 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: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.6901        | 1.0   | 76   | 2.9966          |
| 1.1272        | 2.0   | 152  | 2.6070          |
| 1.0337        | 3.0   | 228  | 2.5657          |
| 0.9638        | 4.0   | 304  | 2.5379          |
| 0.9419        | 5.0   | 380  | 2.5376          |
| 0.9117        | 6.0   | 456  | 2.5333          |
| 0.8944        | 7.0   | 532  | 2.5417          |
| 0.8824        | 8.0   | 608  | 2.5474          |
| 0.8759        | 9.0   | 684  | 2.5541          |
| 0.8735        | 10.0  | 760  | 2.5524          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1