---
base_model: google/gemma-2-2b-it
library_name: peft
license: gemma
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Gemma-2b-MultiCap-mt
  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-MultiCap-mt

This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8644

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1429        | 0.1277 | 50   | 1.1222          |
| 0.8782        | 0.2554 | 100  | 0.9298          |
| 0.8032        | 0.3831 | 150  | 0.8972          |
| 0.9111        | 0.5109 | 200  | 0.8814          |
| 0.8477        | 0.6386 | 250  | 0.8734          |
| 0.8528        | 0.7663 | 300  | 0.8679          |
| 0.8024        | 0.8940 | 350  | 0.8644          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1