---
base_model: google/gemma-2-2b-it
library_name: peft
license: gemma
metrics:
- accuracy
- f1
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: PaperPrism_gemma2
  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. -->

# PaperPrism_gemma2

This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2055
- Accuracy: 0.7476
- F1: 0.7142
- Precision: 0.7845
- Recall: 0.7476

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 0.0300 | 100  | 1.5942          | 0.7248   | 0.7061 | 0.7081    | 0.7248 |
| No log        | 0.0601 | 200  | 1.6005          | 0.7524   | 0.7241 | 0.7486    | 0.7524 |
| No log        | 0.0901 | 300  | 1.4531          | 0.7656   | 0.7506 | 0.7555    | 0.7656 |
| No log        | 0.1202 | 400  | 1.8157          | 0.7332   | 0.7134 | 0.7484    | 0.7332 |
| 0.591         | 0.1502 | 500  | 1.4562          | 0.7825   | 0.7753 | 0.7774    | 0.7825 |
| 0.591         | 0.1803 | 600  | 1.3786          | 0.7692   | 0.7636 | 0.7816    | 0.7692 |
| 0.591         | 0.2103 | 700  | 2.2055          | 0.7476   | 0.7142 | 0.7845    | 0.7476 |


### Framework versions

- PEFT 0.13.0
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0