---
license: cc-by-4.0
base_model: deepset/roberta-base-squad2
tags:
- generated_from_trainer
model-index:
- name: roberta-base-squad2-finetuned-newqa1
  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. -->

# roberta-base-squad2-finetuned-newqa1

This model is a fine-tuned version of [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.3201

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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   | 66   | 2.2730          |
| No log        | 2.0   | 132  | 1.9853          |
| No log        | 3.0   | 198  | 2.0627          |
| No log        | 4.0   | 264  | 2.3190          |
| No log        | 5.0   | 330  | 2.5382          |
| No log        | 6.0   | 396  | 3.0129          |
| No log        | 7.0   | 462  | 3.0762          |
| 1.127         | 8.0   | 528  | 3.3226          |
| 1.127         | 9.0   | 594  | 3.4531          |
| 1.127         | 10.0  | 660  | 3.9486          |
| 1.127         | 11.0  | 726  | 3.7776          |
| 1.127         | 12.0  | 792  | 3.5990          |
| 1.127         | 13.0  | 858  | 3.7593          |
| 1.127         | 14.0  | 924  | 4.0871          |
| 1.127         | 15.0  | 990  | 4.0839          |
| 0.1163        | 16.0  | 1056 | 4.2244          |
| 0.1163        | 17.0  | 1122 | 4.2595          |
| 0.1163        | 18.0  | 1188 | 4.3196          |
| 0.1163        | 19.0  | 1254 | 4.3051          |
| 0.1163        | 20.0  | 1320 | 4.3201          |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3