---
license: gemma
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
datasets:
- generator
base_model: google/gemma-2b
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
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# 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: 2.1557

## Model description

Fine-tuning learning progress.

## Training and evaluation data

Fine tuned on databricks-dolly-15k with LoRa

## Training procedure

Everything took place on the Intel Developer Cloud. Was fine tuned on Intel(R) Data Center GPU Max 1100.

### 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: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 593

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.8555        | 0.82  | 100  | 2.5404          |
| 2.4487        | 1.64  | 200  | 2.3221          |
| 2.3054        | 2.46  | 300  | 2.2302          |
| 2.2362        | 3.28  | 400  | 2.1790          |
| 2.197         | 4.1   | 500  | 2.1557          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.0.1a0+cxx11.abi
- Datasets 2.18.0
- Tokenizers 0.15.2