---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base-riddle-finetuned_new
  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-riddle-finetuned_new

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3192
- Accuracy: 0.8500

## 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: 0.0005
- 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 23   | 0.4749          | 0.75     |
| No log        | 2.0   | 46   | 0.4396          | 0.7750   |
| No log        | 3.0   | 69   | 0.4988          | 0.7750   |
| No log        | 4.0   | 92   | 0.4534          | 0.8000   |
| No log        | 5.0   | 115  | 0.4505          | 0.8250   |
| No log        | 6.0   | 138  | 0.4108          | 0.8250   |
| No log        | 7.0   | 161  | 0.4701          | 0.8000   |
| No log        | 8.0   | 184  | 0.4327          | 0.8250   |
| No log        | 9.0   | 207  | 0.5293          | 0.8000   |
| No log        | 10.0  | 230  | 0.5596          | 0.7750   |
| No log        | 11.0  | 253  | 0.4872          | 0.9000   |
| No log        | 12.0  | 276  | 0.3860          | 0.8500   |
| No log        | 13.0  | 299  | 0.4549          | 0.9000   |
| No log        | 14.0  | 322  | 0.4340          | 0.8250   |
| No log        | 15.0  | 345  | 0.4540          | 0.7750   |
| No log        | 16.0  | 368  | 0.5259          | 0.75     |
| No log        | 17.0  | 391  | 0.3192          | 0.8500   |
| No log        | 18.0  | 414  | 0.3699          | 0.875    |
| No log        | 19.0  | 437  | 0.3577          | 0.875    |
| No log        | 20.0  | 460  | 0.4405          | 0.8250   |
| No log        | 21.0  | 483  | 0.5207          | 0.8250   |
| 0.1396        | 22.0  | 506  | 0.4686          | 0.8000   |
| 0.1396        | 23.0  | 529  | 0.4614          | 0.875    |
| 0.1396        | 24.0  | 552  | 0.4442          | 0.8250   |
| 0.1396        | 25.0  | 575  | 0.4242          | 0.8250   |
| 0.1396        | 26.0  | 598  | 0.4943          | 0.8000   |
| 0.1396        | 27.0  | 621  | 0.4973          | 0.8500   |
| 0.1396        | 28.0  | 644  | 0.4542          | 0.875    |
| 0.1396        | 29.0  | 667  | 0.4671          | 0.875    |
| 0.1396        | 30.0  | 690  | 0.4679          | 0.875    |


### Framework versions

- Transformers 4.36.2
- Pytorch 1.13.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.0