transformers tensorboard safetensors roberta question-answering generated_from_trainer dataset:germanquad endpoints_compatible region:us
---
tags:
- generated_from_trainer
datasets:
- germanquad
model-index:
- name: GQA_RoBERTa
  results: []
---

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# GQA_RoBERTa

This model was trained from scratch on the germanquad dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8389

## 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: 128
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 90   | 5.4929          |
| No log        | 2.0   | 180  | 5.5185          |
| No log        | 3.0   | 270  | 5.3102          |
| No log        | 4.0   | 360  | 4.9559          |
| No log        | 5.0   | 450  | 4.6422          |
| 4.3295        | 6.0   | 540  | 4.3858          |
| 4.3295        | 7.0   | 630  | 4.1523          |
| 4.3295        | 8.0   | 720  | 4.0114          |
| 4.3295        | 9.0   | 810  | 3.5878          |
| 4.3295        | 10.0  | 900  | 3.6762          |
| 4.3295        | 11.0  | 990  | 3.7009          |
| 2.719         | 12.0  | 1080 | 3.7030          |
| 2.719         | 13.0  | 1170 | 3.9876          |
| 2.719         | 14.0  | 1260 | 3.7367          |
| 2.719         | 15.0  | 1350 | 3.7522          |
| 2.719         | 16.0  | 1440 | 3.6393          |
| 2.0323        | 17.0  | 1530 | 3.7502          |
| 2.0323        | 18.0  | 1620 | 3.8672          |
| 2.0323        | 19.0  | 1710 | 3.8356          |
| 2.0323        | 20.0  | 1800 | 3.8389          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.7
- Tokenizers 0.15.0
