transformers pytorch bert text-classification generated_from_trainer dataset:imdb license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- imdb
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: finetuned-base_small_db
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: imdb
      type: imdb
      config: plain_text
      split: train
      args: plain_text
    metrics:
    - type: accuracy
      value: 0.93512
      name: Accuracy
    - type: f1
      value: 0.9664723634709991
      name: F1
---

<!-- 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. -->

# finetuned-base_small_db

This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2838
- Accuracy: 0.9351
- F1: 0.9665

## 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: 3e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.2743        | 2.55  | 500  | 0.1548          | 0.9408   | 0.9695 |
| 0.1227        | 5.1   | 1000 | 0.2545          | 0.9206   | 0.9586 |
| 0.0569        | 7.65  | 1500 | 0.4467          | 0.8902   | 0.9419 |
| 0.0316        | 10.2  | 2000 | 0.2838          | 0.9351   | 0.9665 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
