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---
license: gemma
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: google/gemma-2b
model-index:
- name: eu-ai-act-align
results: []
pipeline_tag: question-answering
---
<!-- 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. -->
# eu-ai-act-align
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on over 1000 questions and answers surrounding the EU AI Act.
It achieves the following results on the evaluation set:
- Loss: 1.7628
## Model description
More information needed
## Intended uses & limitations
It is intended to be used as a preliminary guide to understading the Act, but detailed information about the act can be verified via official public documents.
## Training and evaluation data
Training was done with 1023 questions and answer pairs and finetuned on the Gemma 2b model.
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.139 | 1.0 | 230 | 1.9804 |
| 1.9368 | 2.0 | 460 | 1.8491 |
| 1.8613 | 3.0 | 690 | 1.8011 |
| 1.8008 | 4.0 | 920 | 1.7763 |
| 1.7447 | 5.0 | 1150 | 1.7634 |
| 1.6942 | 6.0 | 1380 | 1.7563 |
| 1.6558 | 7.0 | 1610 | 1.7513 |
| 1.6192 | 8.0 | 1840 | 1.7446 |
| 1.5782 | 9.0 | 2070 | 1.7573 |
| 1.5463 | 10.0 | 2300 | 1.7628 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |