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---
license: gemma
library_name: peft
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
base_model: google/gemma-2b
datasets:
- llama-duo/synth_summarize_dataset_dedup
model-index:
- name: gemma2b-summarize-claude3sonnet-128k
  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. -->

# gemma2b-summarize-claude3sonnet-128k

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the llama-duo/synth_summarize_dataset_dedup dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6928

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 2
- total_train_batch_size: 48
- total_eval_batch_size: 24
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0192        | 1.0   | 402  | 2.4514          |
| 0.9424        | 2.0   | 804  | 2.4604          |
| 0.8955        | 3.0   | 1206 | 2.5064          |
| 0.8659        | 4.0   | 1608 | 2.5306          |
| 0.8359        | 5.0   | 2010 | 2.5706          |
| 0.7986        | 6.0   | 2412 | 2.6196          |
| 0.7778        | 7.0   | 2814 | 2.6583          |
| 0.7562        | 8.0   | 3216 | 2.6846          |
| 0.7563        | 9.0   | 3618 | 2.6927          |
| 0.7461        | 10.0  | 4020 | 2.6928          |


### Framework versions

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