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---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: N_roberta_imdb_padding90model
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: 0.951
---
<!-- 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_padding90model
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: 0.4435
- Accuracy: 0.951
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.21 | 1.0 | 1563 | 0.2359 | 0.9291 |
| 0.1649 | 2.0 | 3126 | 0.1754 | 0.9488 |
| 0.1154 | 3.0 | 4689 | 0.2331 | 0.944 |
| 0.0712 | 4.0 | 6252 | 0.2467 | 0.9473 |
| 0.0609 | 5.0 | 7815 | 0.3661 | 0.9428 |
| 0.0473 | 6.0 | 9378 | 0.3834 | 0.9435 |
| 0.0218 | 7.0 | 10941 | 0.4244 | 0.9434 |
| 0.0205 | 8.0 | 12504 | 0.4267 | 0.9446 |
| 0.0154 | 9.0 | 14067 | 0.3937 | 0.9460 |
| 0.0172 | 10.0 | 15630 | 0.4532 | 0.9476 |
| 0.0157 | 11.0 | 17193 | 0.4495 | 0.9462 |
| 0.0125 | 12.0 | 18756 | 0.4728 | 0.9452 |
| 0.0109 | 13.0 | 20319 | 0.4407 | 0.9494 |
| 0.0083 | 14.0 | 21882 | 0.4388 | 0.9474 |
| 0.0032 | 15.0 | 23445 | 0.4751 | 0.9467 |
| 0.0039 | 16.0 | 25008 | 0.4764 | 0.9481 |
| 0.0001 | 17.0 | 26571 | 0.4742 | 0.9501 |
| 0.0027 | 18.0 | 28134 | 0.4530 | 0.9509 |
| 0.0024 | 19.0 | 29697 | 0.4451 | 0.9508 |
| 0.0033 | 20.0 | 31260 | 0.4435 | 0.951 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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