transformers pytorch bert text-classification generated_from_trainer dataset:imdb base_model:google-bert/bert-base-uncased base_model:finetune:google-bert/bert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: bert-base-uncased
datasets:
- imdb
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: N_bert_imdb_padding60model
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: imdb
      type: imdb
      config: plain_text
      split: test
      args: plain_text
    metrics:
    - type: accuracy
      value: 0.9378
      name: Accuracy
---

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# N_bert_imdb_padding60model

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: 0.7025
- Accuracy: 0.9378

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2209        | 1.0   | 1563  | 0.2386          | 0.92     |
| 0.1627        | 2.0   | 3126  | 0.2066          | 0.9349   |
| 0.0902        | 3.0   | 4689  | 0.3334          | 0.9260   |
| 0.0574        | 4.0   | 6252  | 0.3642          | 0.9349   |
| 0.0448        | 5.0   | 7815  | 0.3988          | 0.9351   |
| 0.0386        | 6.0   | 9378  | 0.4496          | 0.9329   |
| 0.014         | 7.0   | 10941 | 0.4423          | 0.9358   |
| 0.0191        | 8.0   | 12504 | 0.4193          | 0.9356   |
| 0.0183        | 9.0   | 14067 | 0.5018          | 0.9337   |
| 0.0111        | 10.0  | 15630 | 0.5163          | 0.9338   |
| 0.0125        | 11.0  | 17193 | 0.5138          | 0.9360   |
| 0.0067        | 12.0  | 18756 | 0.5259          | 0.9360   |
| 0.006         | 13.0  | 20319 | 0.6622          | 0.9314   |
| 0.0042        | 14.0  | 21882 | 0.6154          | 0.9348   |
| 0.004         | 15.0  | 23445 | 0.6094          | 0.9345   |
| 0.0031        | 16.0  | 25008 | 0.6450          | 0.9356   |
| 0.0013        | 17.0  | 26571 | 0.6317          | 0.9384   |
| 0.0014        | 18.0  | 28134 | 0.6713          | 0.9386   |
| 0.0           | 19.0  | 29697 | 0.6938          | 0.9383   |
| 0.0006        | 20.0  | 31260 | 0.7025          | 0.9378   |


### Framework versions

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