---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: bert_uncased_L-2_H-128_A-2-finetuned-emotion-finetuned-tweet
  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: 0.87168
    - name: F1
      type: f1
      value: 0.8716747437975058
---

<!-- 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. -->

# bert_uncased_L-2_H-128_A-2-finetuned-emotion-finetuned-tweet

This model is a fine-tuned version of [muhtasham/bert_uncased_L-2_H-128_A-2-finetuned-emotion](https://huggingface.co/muhtasham/bert_uncased_L-2_H-128_A-2-finetuned-emotion) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4004
- Accuracy: 0.8717
- F1: 0.8717

## 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: 64
- eval_batch_size: 64
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4751        | 1.28  | 500  | 0.3880          | 0.828    | 0.8277 |
| 0.3453        | 2.56  | 1000 | 0.3282          | 0.8608   | 0.8607 |
| 0.2973        | 3.84  | 1500 | 0.3140          | 0.8695   | 0.8695 |
| 0.26          | 5.12  | 2000 | 0.3154          | 0.8736   | 0.8735 |
| 0.2218        | 6.39  | 2500 | 0.3144          | 0.8756   | 0.8756 |
| 0.1977        | 7.67  | 3000 | 0.3197          | 0.876    | 0.8760 |
| 0.1656        | 8.95  | 3500 | 0.3526          | 0.8737   | 0.8735 |
| 0.1404        | 10.23 | 4000 | 0.3865          | 0.8691   | 0.8689 |
| 0.121         | 11.51 | 4500 | 0.4004          | 0.8717   | 0.8717 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2