peft tensorboard safetensors trl sft generated_from_trainer base_model:google/gemma-7b-it license:other region:us
---
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-english-brainstorming
  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-english-brainstorming

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: 2.3974
- Rouge Scores: {'rouge1': 0.8672818649395687, 'rouge2': 0.6454332350275582, 'rougeL': 0.6351345254871303, 'rougeLsum': 0.8672626398857906}
- Bleu Scores: [0.8956480474494563, 0.8706364987273697, 0.8304269359390679, 0.785372823061285]
- Gen Len: 170.6158

## 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  |
|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------:|:--------:|
| 2.3012        | 1.0   | 398  | 2.0026          | {'rouge1': 0.8605967894222545, 'rouge2': 0.636131431928223, 'rougeL': 0.6291428969983008, 'rougeLsum': 0.860624331598749}   | [0.8793248327807496, 0.8543278363738773, 0.8139923136639805, 0.7687265678282116] | 170.5932 |
| 1.2054        | 2.0   | 796  | 2.0260          | {'rouge1': 0.8587397434055452, 'rouge2': 0.6353005312218787, 'rougeL': 0.6345388735413529, 'rougeLsum': 0.8588818459220777} | [0.874882697664012, 0.8507131493229504, 0.8111205664503656, 0.7665706439816697]  | 170.6271 |
| 0.519         | 3.0   | 1194 | 2.3974          | {'rouge1': 0.8672818649395687, 'rouge2': 0.6454332350275582, 'rougeL': 0.6351345254871303, 'rougeLsum': 0.8672626398857906} | [0.8956480474494563, 0.8706364987273697, 0.8304269359390679, 0.785372823061285]  | 170.6158 |


### Framework versions

- PEFT 0.9.1.dev0
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.18.1.dev0
- Tokenizers 0.15.2