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_padding100model
  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: 0.93724
      name: Accuracy
---

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# N_bert_imdb_padding100model

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: 0.7094
- Accuracy: 0.9372

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2271        | 1.0   | 1563  | 0.2627          | 0.9098   |
| 0.1657        | 2.0   | 3126  | 0.2289          | 0.9296   |
| 0.0928        | 3.0   | 4689  | 0.3241          | 0.9247   |
| 0.0656        | 4.0   | 6252  | 0.3616          | 0.9314   |
| 0.045         | 5.0   | 7815  | 0.3673          | 0.9310   |
| 0.034         | 6.0   | 9378  | 0.4597          | 0.9307   |
| 0.0202        | 7.0   | 10941 | 0.4430          | 0.9364   |
| 0.0188        | 8.0   | 12504 | 0.5484          | 0.9296   |
| 0.0144        | 9.0   | 14067 | 0.5043          | 0.9344   |
| 0.0115        | 10.0  | 15630 | 0.5540          | 0.9336   |
| 0.0094        | 11.0  | 17193 | 0.4962          | 0.9338   |
| 0.0066        | 12.0  | 18756 | 0.5736          | 0.9364   |
| 0.0068        | 13.0  | 20319 | 0.6779          | 0.9335   |
| 0.0038        | 14.0  | 21882 | 0.6431          | 0.9355   |
| 0.0021        | 15.0  | 23445 | 0.6151          | 0.9359   |
| 0.0009        | 16.0  | 25008 | 0.7113          | 0.9348   |
| 0.0           | 17.0  | 26571 | 0.7734          | 0.9336   |
| 0.003         | 18.0  | 28134 | 0.7006          | 0.9372   |
| 0.0008        | 19.0  | 29697 | 0.7140          | 0.9374   |
| 0.0           | 20.0  | 31260 | 0.7094          | 0.9372   |


### Framework versions

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