---
license: other
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: google/gemma-7b-it
model-index:
- name: gemma-7b-it-dolly-15k-japanese-brainstorming-ipo
  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. -->

# gemma-7b-it-dolly-15k-japanese-brainstorming-ipo

This model is a fine-tuned version of [google/gemma-7b-it](https://huggingface.co/google/gemma-7b-it) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4864
- Rouge Scores: {'rouge1': 0.8349379511354852, 'rouge2': 0.7274477012465996, 'rougeL': 0.8017731965466872, 'rougeLsum': 0.8347274626949961}
- Bleu Scores: [0.8344549267092076, 0.7702670675251023, 0.7108107057859971, 0.6501643333897235]
- Gen Len: 241.8588

## 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: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge Scores                                                                                                                | Bleu Scores                                                                      | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------:|:--------:|
| 2.6263        | 1.0   | 398  | 2.3289          | {'rouge1': 0.8429091284800581, 'rouge2': 0.6936436106699162, 'rougeL': 0.8148324021885509, 'rougeLsum': 0.8436115528203997} | [0.8182599825705432, 0.7573989130361584, 0.6993616529579798, 0.6397083137823109] | 241.8588 |
| 1.4454        | 2.0   | 796  | 2.2673          | {'rouge1': 0.8676191825821662, 'rouge2': 0.7714826591897748, 'rougeL': 0.8384600375456672, 'rougeLsum': 0.8676504211460437} | [0.838231259049653, 0.7749860292910674, 0.715811357776676, 0.6553787760578684]   | 241.8588 |
| 0.6829        | 3.0   | 1194 | 2.4864          | {'rouge1': 0.8349379511354852, 'rouge2': 0.7274477012465996, 'rougeL': 0.8017731965466872, 'rougeLsum': 0.8347274626949961} | [0.8344549267092076, 0.7702670675251023, 0.7108107057859971, 0.6501643333897235] | 241.8588 |


### Framework versions

- PEFT 0.8.2
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.2.dev0
- Tokenizers 0.15.2