---
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-gpt4o-256k
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# gemma2b-summarize-gpt4o-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: 2.5990

## 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: 4
- total_train_batch_size: 96
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.1174        | 0.9974 | 292  | 2.4482          |
| 1.0252        | 1.9983 | 585  | 2.4514          |
| 0.988         | 2.9991 | 878  | 2.4683          |
| 0.9741        | 4.0    | 1171 | 2.5000          |
| 0.9342        | 4.9974 | 1463 | 2.5203          |
| 0.9201        | 5.9983 | 1756 | 2.5519          |
| 0.9054        | 6.9991 | 2049 | 2.5763          |
| 0.8902        | 8.0    | 2342 | 2.5922          |
| 0.8818        | 8.9974 | 2634 | 2.5982          |
| 0.8852        | 9.9744 | 2920 | 2.5990          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1