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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-gemini1_5flash-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. -->

# gemma7b-summarize-gemini1_5flash-256k

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: 2.4690

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.9973        | 0.9988 | 414  | 2.5221          |
| 0.9036        | 2.0    | 829  | 2.4358          |
| 0.7651        | 2.9988 | 1243 | 2.3987          |
| 0.7192        | 4.0    | 1658 | 2.3970          |
| 0.6986        | 4.9988 | 2072 | 2.4163          |
| 0.6737        | 6.0    | 2487 | 2.4236          |
| 0.6633        | 6.9988 | 2901 | 2.4494          |
| 0.661         | 8.0    | 3316 | 2.4621          |
| 0.643         | 8.9988 | 3730 | 2.4791          |
| 0.6511        | 9.9879 | 4140 | 2.4690          |


### Framework versions

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