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---
license: gemma
library_name: peft
tags:
- generated_from_trainer
base_model: google/gemma-2b-it
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: gemma-ai-detect-v1
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-ai-detect-v1
This model is a fine-tuned version of [google/gemma-2b-it](https://huggingface.co/google/gemma-2b-it) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1378
- Accuracy: 0.9612
- F1: 0.9689
- Precision: 0.9700
- Recall: 0.9678
## 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: 0.0006
- train_batch_size: 192
- eval_batch_size: 192
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log | 1.0 | 209 | 0.1632 | 0.9322 | 0.9472 | 0.9214 | 0.9745 |
| No log | 2.0 | 418 | 0.1209 | 0.9524 | 0.9617 | 0.9665 | 0.9569 |
| 0.2181 | 3.0 | 627 | 0.1280 | 0.9512 | 0.9608 | 0.9627 | 0.9590 |
| 0.2181 | 4.0 | 836 | 0.1378 | 0.9612 | 0.9689 | 0.9700 | 0.9678 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.5.1+cu124
- Datasets 2.18.0
- Tokenizers 0.19.1 |