---
license: mit
base_model: deepset/gelectra-large-germanquad
tags:
- generated_from_trainer
model-index:
- name: Finetuned_Question_Answering_Model
  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. -->

# Finetuned_Question_Answering_Model

This model is a fine-tuned version of [deepset/gelectra-large-germanquad](https://huggingface.co/deepset/gelectra-large-germanquad) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0331

## 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: 5
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1008        | 1.0   | 3    | 0.3691          |
| 0.177         | 2.0   | 6    | 0.2874          |
| 0.0763        | 3.0   | 9    | 0.2115          |
| 0.0065        | 4.0   | 12   | 0.1496          |
| 0.0075        | 5.0   | 15   | 0.0874          |
| 0.0231        | 6.0   | 18   | 0.0727          |
| 0.0059        | 7.0   | 21   | 0.0512          |
| 0.0302        | 8.0   | 24   | 0.0407          |
| 0.0017        | 9.0   | 27   | 0.0347          |
| 0.0015        | 10.0  | 30   | 0.0331          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2