---
base_model: google/gemma-2b
library_name: peft
license: gemma
metrics:
- accuracy
tags:
- trl
- reward-trainer
- generated_from_trainer
model-index:
- name: run-gemma
  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. -->

# run-gemma

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4238
- Accuracy: 0.7778

## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 200

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.7031        | 0.1087 | 10   | 0.6740          | 0.5752   |
| 0.6719        | 0.2174 | 20   | 0.6701          | 0.6046   |
| 0.6602        | 0.3261 | 30   | 0.6497          | 0.6601   |
| 0.6367        | 0.4348 | 40   | 0.6113          | 0.7059   |
| 0.6172        | 0.5435 | 50   | 0.5686          | 0.7320   |
| 0.5625        | 0.6522 | 60   | 0.5276          | 0.7451   |
| 0.5664        | 0.7609 | 70   | 0.4938          | 0.7451   |
| 0.5859        | 0.8696 | 80   | 0.4651          | 0.7712   |
| 0.5           | 0.9783 | 90   | 0.4560          | 0.7647   |
| 0.5898        | 1.0870 | 100  | 0.4560          | 0.7582   |
| 0.5664        | 1.1957 | 110  | 0.4459          | 0.7516   |
| 0.4648        | 1.3043 | 120  | 0.4387          | 0.7745   |
| 0.5117        | 1.4130 | 130  | 0.4306          | 0.7712   |
| 0.4219        | 1.5217 | 140  | 0.4239          | 0.7680   |
| 0.3828        | 1.6304 | 150  | 0.4314          | 0.7680   |
| 0.3789        | 1.7391 | 160  | 0.4319          | 0.7647   |
| 0.3828        | 1.8478 | 170  | 0.4291          | 0.7680   |
| 0.3438        | 1.9565 | 180  | 0.4279          | 0.7745   |
| 0.3496        | 2.0652 | 190  | 0.4274          | 0.7712   |
| 0.3945        | 2.1739 | 200  | 0.4238          | 0.7778   |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1