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---
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
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