---
license: gemma
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: google/gemma-2b
datasets:
- generator
model-index:
- name: gemma-2b-dolly-qa
  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-2b-dolly-qa

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0226

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 1480

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 2.9171        | 1.6393  | 100  | 2.5622          |
| 2.4316        | 3.2787  | 200  | 2.2899          |
| 2.2671        | 4.9180  | 300  | 2.1729          |
| 2.16          | 6.5574  | 400  | 2.1081          |
| 2.1232        | 8.1967  | 500  | 2.0763          |
| 2.0816        | 9.8361  | 600  | 2.0586          |
| 2.07          | 11.4754 | 700  | 2.0476          |
| 2.0527        | 13.1148 | 800  | 2.0396          |
| 2.0445        | 14.7541 | 900  | 2.0343          |
| 2.0375        | 16.3934 | 1000 | 2.0300          |
| 2.0299        | 18.0328 | 1100 | 2.0270          |
| 2.0231        | 19.6721 | 1200 | 2.0248          |
| 2.0165        | 21.3115 | 1300 | 2.0233          |
| 2.0221        | 22.9508 | 1400 | 2.0226          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.1.0.post0+cxx11.abi
- Datasets 2.19.0
- Tokenizers 0.19.1