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---
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: 0.0316
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.0762 | 1.0 | 3 | 0.3330 |
| 0.5877 | 2.0 | 6 | 0.2301 |
| 0.0194 | 3.0 | 9 | 0.1833 |
| 0.1341 | 4.0 | 12 | 0.0951 |
| 0.002 | 5.0 | 15 | 0.0650 |
| 0.1363 | 6.0 | 18 | 0.0458 |
| 0.0263 | 7.0 | 21 | 0.0385 |
| 0.0032 | 8.0 | 24 | 0.0349 |
| 0.0036 | 9.0 | 27 | 0.0328 |
| 0.0031 | 10.0 | 30 | 0.0316 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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