---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: mini-vanilla-target-imdb
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: imdb
      type: imdb
      config: plain_text
      split: train
      args: plain_text
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.87528
    - name: F1
      type: f1
      value: 0.9334925984386332
---

<!-- 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. -->

# mini-vanilla-target-imdb

This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4773
- Accuracy: 0.8753
- F1: 0.9335

## 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: 32
- eval_batch_size: 32
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4272        | 0.64  | 500  | 0.2066          | 0.92     | 0.9583 |
| 0.299         | 1.28  | 1000 | 0.2608          | 0.8906   | 0.9422 |
| 0.2533        | 1.92  | 1500 | 0.1706          | 0.9337   | 0.9657 |
| 0.2126        | 2.56  | 2000 | 0.3601          | 0.8576   | 0.9233 |
| 0.1913        | 3.2   | 2500 | 0.3955          | 0.8594   | 0.9244 |
| 0.1541        | 3.84  | 3000 | 0.1432          | 0.9484   | 0.9735 |
| 0.1432        | 4.48  | 3500 | 0.2027          | 0.9346   | 0.9662 |
| 0.1256        | 5.12  | 4000 | 0.3797          | 0.8898   | 0.9417 |
| 0.1026        | 5.75  | 4500 | 0.4773          | 0.8753   | 0.9335 |


### Framework versions

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