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---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base-sst-2-32-13-30
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-sst-2-32-13-30
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: 0.5496
- Accuracy: 0.75
## 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: 1.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 2 | 0.6930 | 0.5156 |
| No log | 2.0 | 4 | 0.6929 | 0.5 |
| No log | 3.0 | 6 | 0.6928 | 0.5 |
| No log | 4.0 | 8 | 0.6925 | 0.5 |
| 0.6955 | 5.0 | 10 | 0.6920 | 0.5 |
| 0.6955 | 6.0 | 12 | 0.6914 | 0.5156 |
| 0.6955 | 7.0 | 14 | 0.6904 | 0.5469 |
| 0.6955 | 8.0 | 16 | 0.6891 | 0.5312 |
| 0.6955 | 9.0 | 18 | 0.6872 | 0.5156 |
| 0.6791 | 10.0 | 20 | 0.6845 | 0.5312 |
| 0.6791 | 11.0 | 22 | 0.6805 | 0.5312 |
| 0.6791 | 12.0 | 24 | 0.6751 | 0.5312 |
| 0.6791 | 13.0 | 26 | 0.6654 | 0.5625 |
| 0.6791 | 14.0 | 28 | 0.6525 | 0.625 |
| 0.6052 | 15.0 | 30 | 0.6347 | 0.6406 |
| 0.6052 | 16.0 | 32 | 0.6130 | 0.6719 |
| 0.6052 | 17.0 | 34 | 0.5903 | 0.6875 |
| 0.6052 | 18.0 | 36 | 0.5770 | 0.6875 |
| 0.6052 | 19.0 | 38 | 0.5569 | 0.7031 |
| 0.3501 | 20.0 | 40 | 0.5333 | 0.75 |
| 0.3501 | 21.0 | 42 | 0.5251 | 0.7344 |
| 0.3501 | 22.0 | 44 | 0.5137 | 0.75 |
| 0.3501 | 23.0 | 46 | 0.5118 | 0.7656 |
| 0.3501 | 24.0 | 48 | 0.5151 | 0.7656 |
| 0.137 | 25.0 | 50 | 0.5202 | 0.7656 |
| 0.137 | 26.0 | 52 | 0.5299 | 0.7656 |
| 0.137 | 27.0 | 54 | 0.5379 | 0.7656 |
| 0.137 | 28.0 | 56 | 0.5433 | 0.75 |
| 0.137 | 29.0 | 58 | 0.5477 | 0.75 |
| 0.0715 | 30.0 | 60 | 0.5496 | 0.75 |
### Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.4.0
- Tokenizers 0.13.3
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