---
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-256k
  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-256k

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: 2.5206

## 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: 15

### Training results

| Training Loss | Epoch   | Step  | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 1.0494        | 0.9994  | 808   | 2.4662          |
| 0.9661        | 2.0     | 1617  | 2.4507          |
| 0.9526        | 2.9994  | 2425  | 2.4659          |
| 0.925         | 4.0     | 3234  | 2.4750          |
| 0.9099        | 4.9994  | 4042  | 2.4839          |
| 0.8939        | 6.0     | 4851  | 2.4936          |
| 0.8795        | 6.9994  | 5659  | 2.5032          |
| 0.8694        | 8.0     | 6468  | 2.5068          |
| 0.8608        | 8.9994  | 7276  | 2.5143          |
| 0.8421        | 10.0    | 8085  | 2.5187          |
| 0.8555        | 10.9994 | 8893  | 2.5196          |
| 0.8442        | 12.0    | 9702  | 2.5193          |
| 0.8621        | 12.9994 | 10510 | 2.5206          |
| 0.8586        | 14.0    | 11319 | 2.5210          |
| 0.8485        | 14.9907 | 12120 | 2.5206          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1