---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: tiny-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: 0.83488
    - name: F1
      type: f1
      value: 0.9100104638995464
---

<!-- 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. -->

# tiny-vanilla-target-imdb

This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4589
- Accuracy: 0.8349
- F1: 0.9100

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5912        | 0.64  | 500  | 0.4160          | 0.8295   | 0.9068 |
| 0.3949        | 1.28  | 1000 | 0.4095          | 0.8228   | 0.9028 |
| 0.3386        | 1.92  | 1500 | 0.2948          | 0.8804   | 0.9364 |
| 0.2993        | 2.56  | 2000 | 0.4798          | 0.7868   | 0.8807 |
| 0.2791        | 3.2   | 2500 | 0.4555          | 0.8205   | 0.9014 |
| 0.2585        | 3.84  | 3000 | 0.2815          | 0.8859   | 0.9395 |
| 0.2371        | 4.48  | 3500 | 0.4446          | 0.8316   | 0.9081 |
| 0.2189        | 5.12  | 4000 | 0.6102          | 0.7693   | 0.8696 |
| 0.1989        | 5.75  | 4500 | 0.4589          | 0.8349   | 0.9100 |


### Framework versions

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