---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: N_bert_imdb_padding0model
  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: 0.94052
---

<!-- 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_padding0model

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: 0.6575
- Accuracy: 0.9405

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2204        | 1.0   | 1563  | 0.2086          | 0.9332   |
| 0.1501        | 2.0   | 3126  | 0.2195          | 0.9356   |
| 0.0871        | 3.0   | 4689  | 0.3156          | 0.935    |
| 0.0555        | 4.0   | 6252  | 0.3170          | 0.9314   |
| 0.0362        | 5.0   | 7815  | 0.3568          | 0.9353   |
| 0.0282        | 6.0   | 9378  | 0.4438          | 0.9380   |
| 0.0199        | 7.0   | 10941 | 0.4900          | 0.9357   |
| 0.0219        | 8.0   | 12504 | 0.4963          | 0.9344   |
| 0.0115        | 9.0   | 14067 | 0.5554          | 0.9333   |
| 0.0078        | 10.0  | 15630 | 0.5974          | 0.9340   |
| 0.0087        | 11.0  | 17193 | 0.6081          | 0.9360   |
| 0.0038        | 12.0  | 18756 | 0.5909          | 0.9322   |
| 0.0096        | 13.0  | 20319 | 0.6002          | 0.9381   |
| 0.0061        | 14.0  | 21882 | 0.5645          | 0.9372   |
| 0.0057        | 15.0  | 23445 | 0.6415          | 0.9388   |
| 0.0019        | 16.0  | 25008 | 0.6901          | 0.9388   |
| 0.0005        | 17.0  | 26571 | 0.7099          | 0.9389   |
| 0.0           | 18.0  | 28134 | 0.7022          | 0.9392   |
| 0.0008        | 19.0  | 29697 | 0.6640          | 0.9398   |
| 0.0           | 20.0  | 31260 | 0.6575          | 0.9405   |


### Framework versions

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