---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: N_bert_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: 0.93852
---

<!-- 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_bert_imdb_padding50model

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7352
- Accuracy: 0.9385

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2185        | 1.0   | 1563  | 0.2445          | 0.9211   |
| 0.1562        | 2.0   | 3126  | 0.1966          | 0.9369   |
| 0.0924        | 3.0   | 4689  | 0.3358          | 0.9287   |
| 0.0576        | 4.0   | 6252  | 0.3586          | 0.9308   |
| 0.0493        | 5.0   | 7815  | 0.3533          | 0.9346   |
| 0.0362        | 6.0   | 9378  | 0.4772          | 0.9287   |
| 0.019         | 7.0   | 10941 | 0.4636          | 0.9328   |
| 0.0282        | 8.0   | 12504 | 0.4084          | 0.9350   |
| 0.0155        | 9.0   | 14067 | 0.4659          | 0.9302   |
| 0.0119        | 10.0  | 15630 | 0.5622          | 0.9342   |
| 0.0074        | 11.0  | 17193 | 0.5651          | 0.9338   |
| 0.0047        | 12.0  | 18756 | 0.5859          | 0.9348   |
| 0.006         | 13.0  | 20319 | 0.6266          | 0.9342   |
| 0.0067        | 14.0  | 21882 | 0.6573          | 0.9308   |
| 0.0044        | 15.0  | 23445 | 0.6579          | 0.9370   |
| 0.0           | 16.0  | 25008 | 0.6971          | 0.9386   |
| 0.0011        | 17.0  | 26571 | 0.7194          | 0.9377   |
| 0.0           | 18.0  | 28134 | 0.7164          | 0.9392   |
| 0.0           | 19.0  | 29697 | 0.7198          | 0.9391   |
| 0.0           | 20.0  | 31260 | 0.7352          | 0.9385   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3