peft safetensors gemma alignment-handbook trl sft generated_from_trainer dataset:satpalsr/hindi-sample base_model:google/gemma-7b license:other 4-bit bitsandbytes region:us
---
license: other
library_name: peft
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
base_model: google/gemma-7b
datasets:
- satpalsr/hindi-sample
model-index:
- name: gemma-sft-qlora
  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-sft-qlora

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the satpalsr/hindi-sample dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6385

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.1537        | 0.99  | 94   | 1.0988          |
| 0.9028        | 1.99  | 189  | 0.8056          |
| 0.6553        | 2.99  | 284  | 0.6577          |
| 0.4936        | 3.96  | 376  | 0.6385          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2