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---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: N_roberta_imdb_padding50model
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
split: test
args: plain_text
metrics:
- name: Accuracy
type: accuracy
value: 0.95304
---
<!-- 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. -->
# N_roberta_imdb_padding50model
This model is a fine-tuned version of [roberta-base](https://huggingface.co./roberta-base) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5385
- Accuracy: 0.9530
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2002 | 1.0 | 1563 | 0.2254 | 0.9357 |
| 0.1628 | 2.0 | 3126 | 0.1732 | 0.9478 |
| 0.115 | 3.0 | 4689 | 0.2905 | 0.9365 |
| 0.0737 | 4.0 | 6252 | 0.2347 | 0.9474 |
| 0.062 | 5.0 | 7815 | 0.3516 | 0.9472 |
| 0.0466 | 6.0 | 9378 | 0.3532 | 0.9452 |
| 0.0295 | 7.0 | 10941 | 0.3115 | 0.9481 |
| 0.0213 | 8.0 | 12504 | 0.4286 | 0.9479 |
| 0.0196 | 9.0 | 14067 | 0.4348 | 0.9483 |
| 0.019 | 10.0 | 15630 | 0.5160 | 0.9376 |
| 0.0177 | 11.0 | 17193 | 0.4682 | 0.9467 |
| 0.004 | 12.0 | 18756 | 0.4670 | 0.9503 |
| 0.0076 | 13.0 | 20319 | 0.4573 | 0.9501 |
| 0.0054 | 14.0 | 21882 | 0.5279 | 0.9504 |
| 0.0055 | 15.0 | 23445 | 0.4883 | 0.9504 |
| 0.0051 | 16.0 | 25008 | 0.4782 | 0.9525 |
| 0.0021 | 17.0 | 26571 | 0.4732 | 0.9527 |
| 0.0007 | 18.0 | 28134 | 0.5154 | 0.9519 |
| 0.0029 | 19.0 | 29697 | 0.5317 | 0.9524 |
| 0.002 | 20.0 | 31260 | 0.5385 | 0.9530 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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