transformers pytorch bert text-classification generated_from_trainer dataset:tweet_eval license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- tweet_eval
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: mini-mlm-imdb-target-tweet
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: tweet_eval
      type: tweet_eval
      config: emotion
      split: train
      args: emotion
    metrics:
    - type: accuracy
      value: 0.767379679144385
      name: Accuracy
    - type: f1
      value: 0.7668830990510893
      name: F1
---

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# mini-mlm-imdb-target-tweet

This model is a fine-tuned version of [muhtasham/mini-mlm-imdb](https://huggingface.co/muhtasham/mini-mlm-imdb) on the tweet_eval dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3042
- Accuracy: 0.7674
- F1: 0.7669

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8543        | 4.9   | 500  | 0.6920          | 0.7674   | 0.7571 |
| 0.3797        | 9.8   | 1000 | 0.7231          | 0.7727   | 0.7709 |
| 0.1668        | 14.71 | 1500 | 0.9171          | 0.7594   | 0.7583 |
| 0.068         | 19.61 | 2000 | 1.1558          | 0.7647   | 0.7642 |
| 0.0409        | 24.51 | 2500 | 1.3042          | 0.7674   | 0.7669 |


### Framework versions

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