---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta_sst2_padding50model
  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_sst2_padding50model

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: 0.5107
- Accuracy: 0.9462

## 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: 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 433  | 0.1735          | 0.9319   |
| 0.327         | 2.0   | 866  | 0.2500          | 0.9336   |
| 0.1893        | 3.0   | 1299 | 0.2987          | 0.9407   |
| 0.1229        | 4.0   | 1732 | 0.3376          | 0.9418   |
| 0.0753        | 5.0   | 2165 | 0.3283          | 0.9484   |
| 0.0496        | 6.0   | 2598 | 0.5720          | 0.9116   |
| 0.0349        | 7.0   | 3031 | 0.4278          | 0.9363   |
| 0.0349        | 8.0   | 3464 | 0.4501          | 0.9379   |
| 0.0254        | 9.0   | 3897 | 0.4728          | 0.9374   |
| 0.0217        | 10.0  | 4330 | 0.4662          | 0.9368   |
| 0.0171        | 11.0  | 4763 | 0.4622          | 0.9418   |
| 0.0082        | 12.0  | 5196 | 0.4804          | 0.9429   |
| 0.0094        | 13.0  | 5629 | 0.4789          | 0.9445   |
| 0.0047        | 14.0  | 6062 | 0.5459          | 0.9423   |
| 0.0047        | 15.0  | 6495 | 0.4672          | 0.9434   |
| 0.009         | 16.0  | 6928 | 0.5178          | 0.9445   |
| 0.0021        | 17.0  | 7361 | 0.5107          | 0.9467   |
| 0.0042        | 18.0  | 7794 | 0.5101          | 0.9445   |
| 0.0053        | 19.0  | 8227 | 0.5043          | 0.9462   |
| 0.0017        | 20.0  | 8660 | 0.5107          | 0.9462   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1
- Datasets 2.12.0
- Tokenizers 0.13.3